Podcast appearances and mentions of eric siegel

What if you could predict who will buy, who will click—or even who might lie or die? In this episode, Ben Owden sits down with Dr. Eric Siegel founder of Machine Learning Week, a globally recognized expert on demystifying machine learning and author of two landmark books, Predictive Analytics and The AI Playbook, Dr. Siegel.They cut through the hype of “AI” to reveal how predictive analytics (the real engine behind so many “AI” claims) is transforming day-to-day business operations—from fraud detection and targeted marketing to life-saving medical breakthroughs. Dr. Siegel explains why machine learning doesn't grant magical crystal-ball power, yet still delivers massive value by accurately tipping the odds at scale. Together, they explore how this technology can help build a world that our kids—indeed, all of us—can thrive in, if we apply it ethically and responsibly.Whether you're a data scientist, a tech-savvy entrepreneur, or just curious about AI's practical impact, this conversation will recalibrate how you see machine learning. Discover why some projects succeed while others fizzle out, how real machine learning differs from inflated notions of “intelligent machines,” and why the secret lies in collaboration, probabilities, and concrete, operational goals—not grandiose futurism.Get a copy of The AI PlaybookImportant Links*Join Thrive in the Middle Today!*Book WhyLead to Train Your Teams*Explore Our ServicesSocial Media*Ben Owden's LinkedIn*Ben Owden's Twitter 

Discover the importance of stakeholder involvement in AI deployments with innovation expert, Eric Siegel, PhD, as he discusses balancing predictive analytics with Generative AI and other AI trends for enterprise success.

It's been 12 years since Thomas H Davenport and DJ Patil first declared data science to be “the sexiest job of the 21st century” and in that time a lot has changed. Universities have started offering data science degrees; the number of data scientists has grown exponentially; and generative AI technologies, such as Chat-GPT and Dall-E have transformed the world.Yet, throughout that time, one thing has remained the same. Most machine learning projects still fail to deploy.However, it's not the technical capabilities of data scientists that let them down – those are now better than ever before. Rather, “it's the lack of a well-established business practice that is almost always to blame.”In this episode, Dr Eric Siegel joins Dr Genevieve Hayes to discuss bizML, the new “gold-standard”, six-step practice he has developed “for ushering machine learning projects from conception to deployment.”Guest BioDr Eric Siegel is a leading machine learning consultant and the CEO and co-founder of Gooder AI. He is also the founder of the long-running Machine Learning Week conference series; author of the bestselling Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie or Die and the recently released The AI Playbook; and host of The Dr Data Show podcast.Highlights(01:21) Challenges in machine learning deployment(05:00) The importance of business involvement in ML projects(15:39) Defining bizML and its steps(25:32) Understanding predictive analytics(26:52) Challenges in model deployment and MLOps(29:12) BizML for generative and causal AI(31:25) Exploring uplift modeling(35:45) Gooder AI: bridging the gap between data science and business value(45:45) Beta testing and future plans for Gooder AI(47:35) Final advice for data scientistsbLinksBizML websiteConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

Genevieve Hayes Consulting Episode 48: Overcoming the Machine Learning Deployment Challenge It's been 12 years since Thomas H Davenport and DJ Patil first declared data science to be “the sexiest job of the 21st century” and in that time a lot has changed. Universities have started offering data science degrees; the number of data scientists has grown exponentially; and generative AI technologies, such as Chat-GPT and Dall-E have transformed the world.Yet, throughout that time, one thing has remained the same. Most machine learning projects still fail to deploy.However, it's not the technical capabilities of data scientists that let them down – those are now better than ever before. Rather, “it's the lack of a well-established business practice that is almost always to blame.”In this episode, Dr Eric Siegel joins Dr Genevieve Hayes to discuss bizML, the new “gold-standard”, six-step practice he has developed “for ushering machine learning projects from conception to deployment.” Guest Bio Dr Eric Siegel is a leading machine learning consultant and the CEO and co-founder of Gooder AI. He is also the founder of the long-running Machine Learning Week conference series; author of the bestselling Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie or Die and the recently released The AI Playbook; and host of The Dr Data Show podcast. Highlights (01:21) Challenges in machine learning deployment(05:00) The importance of business involvement in ML projects(15:39) Defining bizML and its steps(25:32) Understanding predictive analytics(26:52) Challenges in model deployment and MLOps(29:12) BizML for generative and causal AI(31:25) Exploring uplift modeling(35:45) Gooder AI: bridging the gap between data science and business value(45:45) Beta testing and future plans for Gooder AI(47:35) Final advice for data scientistsb Links BizML website Connect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE The post Episode 48: Overcoming the Machine Learning Deployment Challenge first appeared on Genevieve Hayes Consulting and is written by Dr Genevieve Hayes.

Eric Siegel has been in the AI field since 1991. He's “horrified” by the AI hype bubble, but not for the reason you may think. Is generative AI the viral sensation we've been promised? Headlines are selling it as a panacea, but 30-year AI industry vet Eric Siegel says that's mostly hype. It may be impressive and introduce efficiencies, but it won't run the world as we've been promised. Predictive AI, Siegel argues, holds all of the transformative potential that we've been guaranteed with generative AI and the LLMs that have become increasingly popular. While generative AI works on a low-level of detail and isn't able to be trusted blindly, predictive AI is fully-autonomous, and can be implemented across a wide range of industries. Here's why Siegel thinks the actual potential lies with predictive modeling, and why we're not going to replicate human intelligence in machines anytime soon. Chapters For Easier Navigation:- 0:00 - The Generative AI illusion 1:05 - Generative AI's function 3:13 - Generative vs. Predictive 4:21 - The Predictive AI process 6:57 - Moving towards AGI? ---------------------------------------------------------------------------------- Go Deeper with Big Think: ►Become a Big Think Member Get exclusive access to full interviews, early access to new releases, Big Think merch and more ►Get Big Think+ for Business Guide, inspire and accelerate leaders at all levels of your company with the biggest minds in business ---------------------------------------------------------------------------------- About Eric Siegel: Eric Siegel is a leading consultant and former Columbia University and UVA Darden professor. He is the founder of the long-running Machine Learning Week conference series, a frequent keynote speaker, and author of The AI Playbook: Mastering the Rare Art of Machine Learning Deployment," as well as the bestselling "Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die." Learn more about your ad choices. Visit megaphone.fm/adchoices

Leading consultant and former Columbia University professor Eric Siegel visits Google to discuss his book “The AI Playbook: Mastering the Rare Art of Machine Learning Deployment.” The book explains how machine learning works and how to successfully operationalize it. The greatest tools are often the hardest to use. Machine learning is the world's most important general-purpose technology – but it's notoriously difficult to launch. Outside Big Tech and a handful of other leading companies, machine learning initiatives routinely fail to deploy, never realizing value. What's missing? A specialized business practice suitable for wide adoption. In "The AI Playbook", bestselling author Eric Siegel presents the gold-standard, six-step practice for ushering machine learning projects from conception to deployment. He illustrates the practice with stories of success and of failure, including revealing case studies from UPS, FICO, and prominent dot-coms. This disciplined approach serves both sides: It empowers business professionals and it establishes a sorely needed strategic framework for data professionals. Beyond detailing the practice, this book also painlessly upskills business professionals. It delivers a vital yet friendly dose of semi-technical background knowledge that all stakeholders need in order to lead or participate in machine learning projects. This puts business and data professionals on the same page so that they can collaborate deeply, jointly establishing precisely what machine learning is called upon to predict, how well it predicts, and how its predictions are acted upon to improve operations. These essentials make or break each initiative – getting them right paves the way for machine learning's value-driven deployment. Visit http://youtube.com/TalksAtGoogle/ to watch the video.                                 

Ever wondered how to truly bridge the gap between technical expertise and practical business implementation? How did the terminology shift from "data mining" to "predictive analytics" and revolutionize the business world? Eric Siegel, Ph.D., is a leading consultant and former Columbia University professor who helps companies deploy machine learning. He is the founder of the long-running Machine Learning Week conference series and the author of several books. His latest work is titled, The AI Playbook: Mastering the Rare Art of Machine Learning Deployment.Eric and Greg discuss what motivated Eric to leave academia to see real-world applications of his machine learning models. Eric explains the pressing challenges organizations face when deploying machine learning projects, and provides an insightful look at the cultural and incentive-driven barriers that often lead to failed projects and unmet expectations. By focusing on collaboration from the outset, Eric reveals how businesses can align machine learning initiatives with their core needs to foster successful integration and operational change.*unSILOed Podcast is produced by University FM.*Episode Quotes:Ramping up on a semi technical understanding of data03:46: Prediction is the most actionable thing you get from data, and the way you get it is with machine learning. Learn some data to predict. That's basically what it is. So, will the world wake up to this? Are they going to forever see it as arcane? What does that mean? So, be careful what you wish for, because flash forward to now, and everyone's all over this stuff in a way that's overzealous. We fetishize the core technology as the most awesome thing. We're more excited about the rocket science than the actual launch of the rocket. That is, getting it deployed, getting into action, making a difference in terms of actual business operations. And we're stuck there. Most new machine learning projects fail to reach deployment. So, still, there's a skill gap. Still, there's a kind of data literacy that's greatly needed across the non-data science community. But it's not foreboding once you actually dip your toe in. As a business stakeholder, you got to get your hands dirty, or your feet will get cold, and you won't get to the point. But that dirty hand stuff, it's only semi-technical. It's totally accessible.Demos don't equal human intelligence36:21: Generative AI is the most amazing thing I've ever seen in my life. But that's the problem. A great demo doesn't necessarily mean valuable, right? I think it's probably about five percent as valuable as the world seems to think, right? So, I mean, I spent six years in the Natural Language Processing Research Group at Columbia, where I was subsequently a professor during graduate school. I never thought I'd see what I can see today, but we need to recognize there's a big difference between something that's seemingly human-like and human.On recognizing change34:53: Do change management because the basic idea is so often overlooked. Again, we're fetishizing the core technology. More excited about the Rock Advanced Launch, but the launch is changed, right? You need to manage that change. The project needs to be reframed. It's not just a technology project. It's not a machine-learning project. It's an operations improvement project that uses machine learning as a core component but ultimately involves improvement, that is to say, change.How do you drive a successful machine learning project?56:38: We need to get everybody on the same page. We need to get those to speak in business terms, and for the business people to be interested in some of those concrete details. Business people might say, "Hey, look, I don't need to get involved in details. I don't need to pop the hood of my car to drive it, right? I don't need to know how the engine works." And that's true. Like, I personally have no idea, right? I know the general principles of internal combustion, but I don't know where the spark plugs are. But I'm totally an expert at driving. I know momentum, friction, the rules of the road, how the car operates, and the mutual expectations of drivers. The analogy holds: to drive a machine learning project successfully through to deployment, you need, analogously, those kinds of semi-technical understanding of what it means to run the project so that it will succeed.Show Links:Recommended Resources:MoneyballArtificial general intelligenceRexer AnalyticsChange ManagementGuest Profile:LinkedIn ProfileMachine Learning WeekGooder.aiHis Work:www.bizML.comMachineLearning.coursesAmazon Author PageThe AI Playbook: Mastering the Rare Art of Machine Learning DeploymentHBR Guide to AI Basics for ManagersPredictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or DieStrategic Analytics: The Insights You Need from Harvard Business ReviewData Science and Business Intelligence: Advice from important Data Scientists around the WorldForbes Articles

Episode 199 Today's topic is AI and ML, and though you may think this doesn't concern marketing, we need to acknowledge how it'll shift things. Up to now, marketing was done on the premise that for a given audience shown a message, some  average percentage, would act on it. With AI, we're now able to look at individual audience members and predict how each of them would act upon a message, and at the opportune moment we could have the message show up to each one of them. Goodbye analyzing what happened with crude audience averages, Hello to using detailed data to predict what's likely to happen.  With AI holding such promise, why don't more companies hand things over to AI? I had thought it's held up by a lack of technical people who know how to do this, but our guest says we've had enough technical expertise - He himself was previously one of those data people, and his expertise wasn't enough to do the job.  He says AI initiatives are held back by those running business functions like marketing who haven't made the business case and collaborated with the data people to implement this.  My guest is a leading consultant and former Columbia University and UVA Darden professor. He is the founder of the long-running Machine Learning Week conference series, a frequent keynote speaker, and author of the bestselling Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die. In 2023 he authored “The AI playbook” Let's talk to Eric Siegel. Links to all people and concepts mentioned are in the shownotes on the Funnel Reboot site.    

Eric Siegel is a former Columbia professor, leading ML consultant & author of The AI Playbook, and Greg Kihlstrom is a CX and marketing technology transformation consultant, author & keynote speaker, as well as the host of The Agile Brand.In this episode, Eric and Greg return to the podcast to discuss how tapping into agile principles would enable businesses and organizations to get more value out of AI and machine learning initiatives.Links & mentions:agiledrop.com/podcast/eric-siegel-are-we-headed-towards-ai-winteragiledrop.com/podcast/greg-kihlstrom-continuous-improvement-ai-customer-experiencelinkedin.com/in/gregkihlstromtheagilebrand.combizml.commachinelearningweek.com

Sue Bethanis hosts Founder of Machine Learning Week, former Columbia professor, and bestselling author, Eric Siegel, Ph.D. Eric is a leading consultant and former Columbia University professor who helps companies deploy machine learning. He is the founder of the long-running Machine Learning Week conference series and its new sister, Generative AI World, the instructor of the acclaimed online course “Machine Learning Leadership and Practice – End-to-End Mastery,” executive editor of The Machine Learning Times, and a frequent keynote speaker. He wrote the bestselling Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, which has been used in courses at hundreds of universities, as well as his newest book, The AI Playbook: Mastering the Rare Art of Machine Learning Deployment.Eric's interdisciplinary work bridges the stubborn technology/business gap. At Columbia, he won the Distinguished Faculty award when teaching graduate computer science courses in ML and AI. Later, he served as a business school professor at UVA Darden. Eric also publishes op-eds on analytics and social justice. He has appeared on numerous media channels, including Bloomberg, National Geographic, and NPR, and has published in Fast Company, Forbes, HBR, Newsweek, The New York Times, WSJ, and more.Sue and Eric dig into his new book, The AI Playbook, and uncover the most vital use cases of machine learning, those designed to improve a wide range of business operations.

Today, Steve is in conversation with AI expert Eric Siegel. A former professor at Columbia University, Eric is the founder of the long-running Machine Learning Week conference series and a bestselling author. His latest book, The AI Playbook, looks at how businesses outside Big Tech can leverage machine learning to grow. He and Steve discuss the differences between generative and predictive AI, the most effective ways to implement AI into an organization's operations, and how we might expect this technology to be useful in the future. Key Takeaways: 1. No matter how controlled or well thought out a project is, any project relying on AI is only as good as its data inputs. 2. The more we learn to differentiate types of AI and apply their functions skillfully, the more we will learn about what is possible.  3. As predictive AI systems emerge, applying quality data analysis to a well chosen project could make a measurable difference for a company's bottom line. Tune in to hear more about: 1. Designing a project involving predictive analytics does require quality data and specific domain areas. (3:00) 2. Generative analytics is still in early stages, and popular notions around its use currently differ from what can reasonably be expected or achieved (4:42) 3. Using AI to work with errors and improve a system requires quality data and carefully applied labels  (11:59) Standout Quotes: 1. “It's absolutely critical to have a fine scope, a reasonable scope, well defined for the first project. But the most well defined, sort of, well, scoped project is, in another way, the biggest because really what we're talking about, if you're looking at what should your first opportunity be with predictive AI that you want to pursue, it should be your largest scale operation that stands to improve the most, and that even an incremental improvement provides a tremendous bottom line. -Eric Siegel 2. “ … It's such a funny time, because predictive and generative are really apples and oranges. They're both built on machine learning, which learns from data to predict. But generative isn't a reference to really something specific in terms of the technology; it's just how you're using it, which is to generate new content items. So, writing a first draft in human language, like English, or of code, or creating a first image or video — these endeavors typically need a human in the loop to review everything that it's generated. They're not autonomous. And the question is, how autonomous could they be?” -Eric Siegel 3.  “You can only predict better than guessing, which turns out to be more than sufficient to drive an improvement to the bottom line. So who's going to click, buy, lie or die, or commit an act of fraud, or turn out to cancel or be a bad debtor? These are human behaviors for those examples, or it could be a corporate client, or it could be a mechanism like a satellite, or the wheel of a train that might fail. But whatever it is, we don't have clairvoyance or a magic crystal ball. We can't expect your computers to, either. So it's about tipping the odds in these numbers games and predicting better than guessing … no matter how good the data is and how devoid of wrong values and those types of errors, you're still going to have that limitation. There's still a ceiling. No matter how advanced the method is, it's not going to become supernatural. There's a thing called chaos theory, which basically says that even if you knew all the neurons of every cell of the person's brain, you wouldn't necessarily be able to predict very far into the future. And of course, we don't. So it's always limited data anyway.” -Eric Siegel 4. “I wrote this new book, The AI Playbook, because we need an organizational practice to make sure that we're sort of planning the project not just technically but organizationally and operationally, so that it actually gets deployed and makes a difference and actually improves operations. And in general, the awareness and understanding of it and how it can be integrated into organizations is still only improving.” -Eric Siegel Mentioned in this episode: ISF Analyst Insight Podcast Read the transcript of this episode Subscribe to the ISF Podcast wherever you listen to podcasts Connect with us on LinkedIn and Twitter From the Information Security Forum, the leading authority on cyber, information security, and risk management.

Today, Steve is in conversation with AI expert Eric Siegel. A former professor at Columbia University, Eric is the founder of the long-running Machine Learning Week conference series and a bestselling author. His latest book, The AI Playbook, looks at how businesses outside Big Tech can leverage machine learning to grow. He and Steve discuss the differences between generative and predictive AI, the most effective ways to implement AI into an organization's operations, and how we might expect this technology to be useful in the future. Key Takeaways: 1. No matter how controlled or well thought out a project is, any project relying on AI is only as good as its data inputs. 2. The more we learn to differentiate types of AI and apply their functions skillfully, the more we will learn about what is possible.  3. As predictive AI systems emerge, applying quality data analysis to a well chosen project could make a measurable difference for a company's bottom line. Tune in to hear more about: 1. Designing a project involving predictive analytics does require quality data and specific domain areas. (3:00) 2. Generative analytics is still in early stages, and popular notions around its use currently differ from what can reasonably be expected or achieved (4:42) 3. Using AI to work with errors and improve a system requires quality data and carefully applied labels  (11:59) Standout Quotes: 1. “It's absolutely critical to have a fine scope, a reasonable scope, well defined for the first project. But the most well defined, sort of, well, scoped project is, in another way, the biggest because really what we're talking about, if you're looking at what should your first opportunity be with predictive AI that you want to pursue, it should be your largest scale operation that stands to improve the most, and that even an incremental improvement provides a tremendous bottom line. -Eric Siegel 2. “ … It's such a funny time, because predictive and generative are really apples and oranges. They're both built on machine learning, which learns from data to predict. But generative isn't a reference to really something specific in terms of the technology; it's just how you're using it, which is to generate new content items. So, writing a first draft in human language, like English, or of code, or creating a first image or video — these endeavors typically need a human in the loop to review everything that it's generated. They're not autonomous. And the question is, how autonomous could they be?” -Eric Siegel 3.  “You can only predict better than guessing, which turns out to be more than sufficient to drive an improvement to the bottom line. So who's going to click, buy, lie or die, or commit an act of fraud, or turn out to cancel or be a bad debtor? These are human behaviors for those examples, or it could be a corporate client, or it could be a mechanism like a satellite, or the wheel of a train that might fail. But whatever it is, we don't have clairvoyance or a magic crystal ball. We can't expect your computers to, either. So it's about tipping the odds in these numbers games and predicting better than guessing … no matter how good the data is and how devoid of wrong values and those types of errors, you're still going to have that limitation. There's still a ceiling. No matter how advanced the method is, it's not going to become supernatural. There's a thing called chaos theory, which basically says that even if you knew all the neurons of every cell of the person's brain, you wouldn't necessarily be able to predict very far into the future. And of course, we don't. So it's always limited data anyway.” -Eric Siegel 4. “I wrote this new book, The AI Playbook, because we need an organizational practice to make sure that we're sort of planning the project not just technically but organizationally and operationally, so that it actually gets deployed and makes a difference and actually improves operations. And in general, the awareness and understanding of it and how it can be integrated into organizations is still only improving.” -Eric Siegel Mentioned in this episode: ISF Analyst Insight Podcast Read the transcript of this episode Subscribe to the ISF Podcast wherever you listen to podcasts Connect with us on LinkedIn and Twitter From the Information Security Forum, the leading authority on cyber, information security, and risk management.

This week on episode 359, we interviewed Paul Daugherty, Chief Technology and Innovation Officer at Accenture and Eric Siegel, Author of The AI Playbook: Mastering the Rare Art of Machine Learning Deployment. DisrupTV is a weekly podcast with hosts R “Ray” Wang and Vala Afshar. The show airs live at 11 AM PT/ 2 PM ET every Friday. Brought to you by Constellation Executive Network: constellationr.com/CEN.

Today we're going to talk about machine learning in the enterprise and how, despite a less than stellar success rate, organizations can achieve success with the right approaches. To help me discuss this topic, I'd like to welcome Eric Siegel, Founder of Machine Learning Week and author of The AI Playbook: Mastering the Rare Art of Machine Learning Deployment. Resources Get The AI Playbook: Mastering the Rare Art of Machine Learning Deployment by Eric Siegel: https://mitpress.mit.edu/9780262048903/the-ai-playbook/ Machine Learning 2024 website: https://machinelearningweek.com/ Sign up for The Agile Brand newsletter here: https://www.gregkihlstrom.com Get the latest news and updates on LinkedIn here: https://www.linkedin.com/company/the-agile-brand/ For consulting on marketing technology, customer experience, and more visit GK5A: https://www.gk5a.com Check out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com The Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://www.teksystems.com/versionnextnow The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company

Today we're going to talk about machine learning in the enterprise and how, despite a less than stellar success rate, organizations can achieve success with the right approaches. To help me discuss this topic, I'd like to welcome Eric Siegel, Founder of Machine Learning Week and author of The AI Playbook: Mastering the Rare Art of Machine Learning Deployment. Resources Get The AI Playbook: Mastering the Rare Art of Machine Learning Deployment by Eric Siegel: https://mitpress.mit.edu/9780262048903/the-ai-playbook/ Machine Learning 2024 website: https://machinelearningweek.com/ Sign up for The Agile Brand newsletter here: https://www.gregkihlstrom.com Get the latest news and updates on LinkedIn here: https://www.linkedin.com/company/the-agile-brand/ For consulting on marketing technology, customer experience, and more visit GK5A: https://www.gk5a.com Check out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com The Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://www.teksystems.com/versionnextnow The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company

Summary Machine learning is a powerful set of technologies, holding the potential to dramatically transform businesses across industries. Unfortunately, the implementation of ML projects often fail to achieve their intended goals. This failure is due to a lack of collaboration and investment across technological and organizational boundaries. To help improve the success rate of machine learning projects Eric Siegel developed the six step bizML framework, outlining the process to ensure that everyone understands the whole process of ML deployment. In this episode he shares the principles and promise of that framework and his motivation for encapsulating it in his book "The AI Playbook". Announcements Hello and welcome to the Machine Learning Podcast, the podcast about machine learning and how to bring it from idea to delivery. Your host is Tobias Macey and today I'm interviewing Eric Siegel about how the bizML approach can help improve the success rate of your ML projects Interview Introduction How did you get involved in machine learning? Can you describe what bizML is and the story behind it? What are the key aspects of this approach that are different from the "industry standard" lifecycle of an ML project? What are the elements of your personal experience as an ML consultant that helped you develop the tenets of bizML? Who are the personas that need to be involved in an ML project to increase the likelihood of success? Who do you find to be best suited to "own" or "lead" the process? What are the organizational patterns that might hinder the work of delivering on the goals of an ML initiative? What are some of the misconceptions about the work involved in/capabilities of an ML model that you commonly encounter? What is your main goal in writing your book "The AI Playbook"? What are the most interesting, innovative, or unexpected ways that you have seen the bizML process in action? What are the most interesting, unexpected, or challenging lessons that you have learned while working on ML projects and developing the bizML framework? When is bizML the wrong choice? What are the future developments in organizational and technical approaches to ML that will improve the success rate of AI projects? Contact Info LinkedIn (https://www.linkedin.com/in/predictiveanalytics/) Parting Question From your perspective, what is the biggest barrier to adoption of machine learning today? Closing Announcements Thank you for listening! Don't forget to check out our other shows. The Data Engineering Podcast (https://www.dataengineeringpodcast.com) covers the latest on modern data management. Podcast.__init__ () covers the Python language, its community, and the innovative ways it is being used. Visit the site (https://www.themachinelearningpodcast.com) to subscribe to the show, sign up for the mailing list, and read the show notes. If you've learned something or tried out a project from the show then tell us about it! Email hosts@themachinelearningpodcast.com (mailto:hosts@themachinelearningpodcast.com)) with your story. To help other people find the show please leave a review on iTunes (https://podcasts.apple.com/us/podcast/the-machine-learning-podcast/id1626358243) and tell your friends and co-workers. Links The AI Playbook (https://www.machinelearningkeynote.com/the-ai-playbook): Mastering the Rare Art of Machine Learning Deployment by Eric Siegel Predictive Analytics (https://www.machinelearningkeynote.com/predictive-analytics): The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel Columbia University (https://www.columbia.edu/) Machine Learning Week Conference (https://machinelearningweek.com/) Generative AI World (https://generativeaiworld.events/) Machine Learning Leadership and Practice Course (https://www.predictiveanalyticsworld.com/machinelearningweek/workshops/machine-learning-course/) Rexer Analytics (https://www.rexeranalytics.com/) KD Nuggets (https://www.kdnuggets.com/) CRISP-DM (https://en.wikipedia.org/wiki/Cross-industry_standard_process_for_data_mining) Random Forest (https://en.wikipedia.org/wiki/Random_forest) Gradient Descent (https://en.wikipedia.org/wiki/Gradient_descent) The intro and outro music is from Hitman's Lovesong feat. Paola Graziano (https://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/Tales_Of_A_Dead_Fish/Hitmans_Lovesong/) by The Freak Fandango Orchestra (http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/)/CC BY-SA 3.0 (https://creativecommons.org/licenses/by-sa/3.0/)

Eric Siegel is a former Columbia professor, leading ML consultant and author of The AI Playbook: Mastering the Rare Art of Machine Learning Deployment, which has just recently been released.In this episode, we talk about whether or not we're headed towards an AI winter and what implications this would have for the future of innovation in artificial intelligence and machine learning. We discuss the law of human-like autonomy and why it is important for these kinds of conversations, and conclude with a look into the future of AI innovation & development.Links & mentions:amazon.com/AI-Playbook-Mastering-Deployment-Managementbizml.comlinkedin.com/in/predictiveanalytics

Eric Siegel, author of the book The AI Playbook, explains what it takes to take traditional and advanced artificial intelligence projects from idea to execution.  

Dr. Eric Siegel is a leading consultant and former Columbia University professor who helps companies deploy machine learning. He is the founder of the long-running Machine Learning Week conference series and its new sister, Generative AI World, the instructor of the acclaimed online course “Machine Learning Leadership and Practice – End-to-End Mastery,” executive editor of The Machine Learning Times, and a frequent keynote speaker. He wrote the bestselling "Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die," which has been used in courses at hundreds of universities, as well as "The AI Playbook: Mastering the Rare Art of Machine Learning Deployment." Eric's interdisciplinary work bridges the stubborn technology/business gap. At Columbia, he won the Distinguished Faculty award when teaching the graduate *computer science* courses in ML and AI. Later, he served as a *business school* professor at UVA Darden. Eric has appeared on numerous media channels, including Bloomberg, National Geographic, and NPR, and has published in Newsweek, HBR, SciAm blog, WaPo, WSJ, and more.Listen and learnHow he's progressed in the field of machine learning over 30 years6-step process to usher in machine learning programs from conception to deployment What 3 things non-technical people in business should know about how machine learning works & delivers valueHow to know when to use classical machine learning vs generative AI to solve a data problemHow to mitigate the impact of human bias in shaping AIResourcesPurchase "The AI Playbook" — http://www.bizML.com Scott Zoldi episode —https://feeds.buzzsprout.com/520474.rss

The most powerful tool often comes with the greatest challenges. In recent times Machine learning has emerged as the world's leading general-purpose technology, yet its implementation remains notably complex. Beyond the realm of Big Tech and a select few leading enterprises, many machine learning initiatives don't succeed, failing to deliver on their potential. What's lacking? A specialised business approach and development & deployment strategy tailored for widespread adoption. In his recent book “The AI Playbook: Mastering the Rare Art of Machine Learning Deployment” acclaimed author Eric Siegel introduces a comprehensive six-step methodology for guiding machine learning projects from inception to implementation. The book showcases the methodology through both successful and unsuccessful anecdotes, featuring insightful case studies from renowned companies such as UPS, FICO, and prominent dot-coms. In this episode of Bridging the Gaps, I speak with Eric Siege. We discuss this disciplined approach that empowers business professionals, and establishes a sorely needed strategic framework for data professionals. Eric Siegel, Ph.D., is a leading consultant and former Columbia University professor who helps companies deploy machine learning. He is the founder of the long-running Machine Learning Week conference series and its new sister, Generative AI World, the instructor of the acclaimed online course “Machine Learning Leadership and Practice – End-to-End Mastery,” executive editor of The Machine Learning Times, and a frequent keynote speaker. We begin our discussion by addressing Eric's notable observation, highlighted both in his presentations and book, that the “AI Hype” is a distraction for companies. Eric elaborates on this notion, providing detailed insights. Additionally, we explore the suggestion to shift focus from the broad term "AI" to the more specific "Machine Learning." Our conversation then delves into the challenges faced by companies and professionals in conceptualising and deploying AI-driven ideas and solutions. This then leads to the consideration of whether forming specialised teams and developing focused strategies are necessary to address these challenges effectively. Next, we delve into the intricacies of the six-step BizML process introduced by Eric in his book, comparing it to the concept of MLOps. We then thoroughly examine the BizML process, dissecting its components and implications. Overall, this has been a highly enlightening and informative discussion. Complement this discussion with ““Working with AI: Real Stories of Human-Machine Collaboration” with Professor Thomas Davenport and Professor Steven Miller” available at: https://www.bridgingthegaps.ie/2022/10/working-with-ai-real-stories-of-human-machine-collaboration-thomas-davenport-steven-miller/ And then listen to ““Machines like Us: TOWARD AI WITH COMMON SENSE” with Professor Ronald Brachman” available at: https://www.bridgingthegaps.ie/2022/06/machines-like-us-toward-ai-with-common-sense-with-professor-ronald-brachman/

The AI Playbook: Mastering the Rare Art of Machine Learning Deployment by Eric Siegel  ABOUT THE BOOK: In his bestselling first book, Eric Siegel explained how machine learning works. Now, in The AI Playbook, he shows how to capitalize on it. The greatest tool is the hardest to use. Machine learning is the world's most important general-purpose technology—but it's notoriously difficult to launch.  Outside Big Tech and a handful of other leading companies, machine learning initiatives routinely fail to deploy, never realizing value.  What's missing? A specialized business practice suitable for wide adoption.  In The AI Playbook, bestselling author Eric Siegel presents the gold-standard, six-step practice for ushering machine learning projects from conception to deployment.  He illustrates the practice with stories of success and of failure, including revealing case studies from UPS, FICO, and prominent dot-coms.  This disciplined approach serves both sides: It empowers business professionals, and it establishes a sorely needed strategic framework for data professionals. Beyond detailing the practice, this book also upskills business professionals—painlessly.  It delivers a vital yet friendly dose of semi-technical background knowledge that all stakeholders need to lead or participate in machine learning projects, end to end.  This puts business and data professionals on the same page so that they can collaborate deeply, jointly establishing precisely what machine learning is called upon to predict, how well it predicts, and how its predictions are acted upon to improve operations.  These essentials make or break each initiative—getting them right paves the way for machine learning's value-driven deployment. A note from the author: What kind of AI does this book cover? The buzzword AI can mean many things, but this book is about machine learning, which is a central basis for—and what many mean by—AI. To be specific, this book covers the most vital use cases of machine learning, those designed to improve a wide range of business operations. ABOUT THE AUTHOR: Eric Siegel, Ph.D. is a leading consultant and former Columbia University professor who helps companies deploy machine learning.  He is the founder of the long-running Machine Learning Week conference series, the instructor of the acclaimed online course “Machine Learning Leadership and Practice – End-to-End Mastery,” executive editor of The Machine Learning Times, and a frequent keynote speaker.  His previous book is the bestselling "Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die," which has been used in courses at hundreds of universities and was featured on episode 74 of The Marketing Book Podcast in 2016. Eric's interdisciplinary work bridges the stubborn technology/business gap. At Columbia, he won the Distinguished Faculty award when teaching graduate computer science courses in ML and AI. Later, he served as a business school professor at the University of Virginia Darden School of Business.  Eric's many media appearances include Bloomberg TV and Radio, Business News Network (Canada), Israel National Radio, NPR Marketplace, Radio National (Australia), Businessweek, CBS MoneyWatch, The European Business Review, The Financial Times, Forbes, Harvard Business Review, The Huffington Post, The New York Times, Newsweek, Scientific American, The Wall Street Journal, and The Washington Post. And, interesting fact – he is a dancing machine!  Click here for this episode's website page with the links mentioned during the interview... https://www.salesartillery.com/marketing-book-podcast/ai-playbook-eric-siegel

Eric Siegel is a seasoned consultant with more than twenty years of experience with machine learning. In today's podcast, Eric shares insights from his best-selling book, "Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die," and his second book, "The AI Playbook." Having taught AI and machine learning at Columbia, he expresses frustration at the underutilization of machine learning. His mission with "The AI Playbook" is to bridge the gap between data scientists and business professionals, emphasizing the need for a customized process, discipline, and playbook for successful machine learning projects. The conversation delves into the misconception surrounding AI and machine learning, emphasizing the importance of planning for business outcomes and operational changes from the project's inception. The guest stresses that the value of AI lies not in its cool factor but in successful deployment. Discussing his second book, he reflects a focus on preorders and an emphasis on podcasts, he shares his strategy for getting the book into the hands of Fortune 500 stakeholders vested in machine learning success. Tune in for an insightful journey into the world of predictive analytics, AI deployment, and the passion that fuels success in the realm of thought leadership. Three Key Takeaways: ·         Business professionals must gain some technical knowledge to establish a standardized practice for machine learning. ·         Understand the use case – what is predicted and how it's acted upon are the cornerstone of driving value in machine learning projects. ·         AI and machine learning are powerful tools but don't get lost in the wonder of them.  Stay focused on what you need them to do for you.

John Wells speaks with George Musser about his new book titled "Putting Ourselves Back in the Equation Why Physicists Are Studying Human Consciousness and AI To Unravel The Mysteries of The Universe."Then, Eric Siegel, author of the new book “The AI Playbook, Mastering the Rare Art of Machine Learning Deployment," talks about how machine learning can enhance business operations.

Watch Carol and Tim LIVE every day on YouTube: http://bit.ly/3vTiACF. Eric Siegel, former Columbia University Professor, discusses his book The AI Playbook: Mastering the Rare Art of Machine Learning Deployment.Hosts: Carol Massar and Tim Stenovec. Producer: Paul Brennan. See omnystudio.com/listener for privacy information.

Watch Carol and Tim LIVE every day on YouTube: http://bit.ly/3vTiACF. Eric Siegel, former Columbia University Professor, discusses his book The AI Playbook: Mastering the Rare Art of Machine Learning Deployment.Hosts: Carol Massar and Tim Stenovec. Producer: Paul Brennan. See omnystudio.com/listener for privacy information.

Despite an abundance of research highlighting the importance of AI in enhancing HR processes, the vast majority of organisations are still at the earliest stages of adoption. Even among those that have already implemented AI in HR, many are using it only for one or two niche applications. This is largely due to the perceived complexity and high costs associated with implementing AI technologies. To tackle this issue, host David Green is joined by Eric Siegel, founder of Machine Learning Week and author of 'The AI Playbook: Monitoring the Rare Art of Machine Learning Deployment' to discuss how organisations can overcome these challenges and effectively integrate AI into their HR functions. Listeners can expect to learn more about: The current state of AI adoption in HR and the barriers to widespread implementation The potential benefits of using AI in HR processes, including improved efficiency and decision-making Practical advice for organisations looking to adopt AI in their HR strategies How HR professionals can prepare for the impact of AI on their roles and responsibilities The role of ethics in AI adoption and how organisations can ensure responsible and ethical use You can also expect to hear about real-world examples of successful AI adoption in HR, as well as insights on the future of AI and its potential impact on the evolution of the HR industry. So tune in to this episode to learn more about how AI can revolutionise HR and what steps your organisation can take to embrace this powerful technology. Support from this podcast comes from ScreenCloud – the digital signage platform that helps HR around the globe elevate their digital employee experience, with 'screens that communicate'. To learn how ScreenCloud can enable your organisation to increase employee engagement, drive productivity and improve compliance, visit screencloud.com Hosted on Acast. See acast.com/privacy for more information.

Best-selling author Eric Siegel discusses his book “The AI Playbook” and the art of machine learning deployment. Eric is a former Columbia University professor who helps companies deploy machine learning. He is the founder of the long-running Machine Learning Week conference series, and executive editor of The Machine Learning Times. In his best-selling first book, "Predictive Analytics” Eric explained how ML works. Now he shows how to capitalize on it. Host, Kevin Craine Do you want to be a guest? DigitalTransformationPodcast.net/guest

Excitement over the prospects for artificial intelligence (AI) has driven US stock market valuations to a historic high. Can AI technologies deliver on their promise? Or is this yet another case of irrational exuberance?In the latest New Money Review podcast I am joined by Eric Siegel, a former Columbia University professor who has taught computer science courses in machine learning and AI. Siegel, now a consultant, has just published a new book called “The AI Playbook—Mastering the Rare Art of Machine Learning Deployment”.In the podcast, we explore some of the paradoxes surrounding AI: why this tech tool with apparently unlimited greatest promise may be the hardest to use, and why computers promising us greater autonomy may in fact require more supervision.We cover:What is artificial intelligence (AI) and what is machine learning (ML)?What is generative AI?What explains the current AI hype?How predictive analytics can improve organisations' performanceExamples of successful machine learning in practice: UPS and credit scoringWhy do so many ML projects fail to reach deployment?Why artificial general intelligence (AGI) is “the most compelling ghost story ever”Why computers that seem more human-like may give us less autonomyWhat goals can ChatGPT reach and where does it fall short?Why AI hype may be costly 

In his new book, The AI Playbook: Mastering the Rare Art of Machine Learning Deployment, Eric Siegel offers a detailed playbook for how business professionals can launch machine learning projects, providing both success stories where private industry got it right as well as cautionary tales others can learn from.Siegel laid out the key findings of his book in our latest episode during a wide-ranging conversation with Marc Ruggiano, director of the University of Virginia's Collaboratory for Applied Data Science in Business, and Michael Albert, an assistant professor of business administration at UVA's Darden School. The discussion, featuring three experts in business analytics, takes an in-depth look at the intersection of artificial intelligence, machine learning, business, and leadership.http://www.bizML.comhttps://www.darden.virginia.edu/faculty-research/centers-initiatives/data-analytics/bodily-professorhttps://pubsonline.informs.org/do/10.1287/LYTX.2023.03.10/full/https://www.kdnuggets.com/survey-machine-learning-projects-still-routinely-fail-to-deployCRISPDM: https://en.wikipedia.org/wiki/Cross-industry_standard_process_for_data_miningCRM: https://en.wikipedia.org/wiki/Customer_relationship_management

In this riveting episode, I sit down with bestselling author and predictive analytics luminary, Eric Siegel. Our discussion unravels the mysteries of his latest book, "The AI Playbook," and takes a no-holds-barred dive into the world of AI. We debunk fallacies, explore the evolving landscape of machine learning, and share insights on why mastering the art is as much about process as it is about technology. Get ready for an honest, entertaining, and enlightening conversation that challenges the way we perceive and navigate the buzzword BIZ ML. Support the showTo sign up for regular updates and the latest research, events, articles, podcasts and more from the Institute of Business Forecasting & Training, visit www.ibf.org

AI deployment is an art and a science. Imagine transforming healthcare with AI. A story unfolds. A hospital implements a machine learning model. Patient outcomes improve dramatically. This is the power of AI when deployed effectively. But let’s delve into the facts. According to Gartner, only 53% of AI projects make it from prototypes to…

Podcast questions and inquiries? Email us: mattandmattoscaletrains@gmail.com New URL for the Podcast: www.mandmpodcast.com Please note: The primary purpose of this Podcast is to educate. We do not constitute advice or services. Please seek advice from an appropriate legal professional in your state, county, or city. Join Matt R, Matt Z, Johnny, and John S as we have a casual conversation about model railroading and life with Eric Siegel and his girlfriend / fiancée Lisa.   Discord Server Link: https://discord.gg/5rpxw8F4DY Please note that you will need to read the rules and click a box to verify that you understand them before you're able to join the server. We want this community to be a welcoming and respectful place.   This Podcast is now available on Spotify and Amazon Music / Audible. We are also available from our usual sources like Apple Podcasts, Google Podcasts, and YouTube.   Spotify: https://open.spotify.com/show/0OOWgO2vvI38ZFOtF4BxkU?si=2a853e2b36a44f80 Google Podcasts: https://bit.ly/3FzsisW Apple Podcasts: https://podcasts.apple.com/us/podcast/the-matt-and-matt-o-scale-trains-podcast/id1527505788 Amazon Music: https://music.amazon.com/podcasts/f8fe369d-985c-4d14-af1f-dc4abf112b06/the-matt-and-matt-o-scale-trains-podcast   The Miniature Models Podcast is now part of the Trainz partner program. If you do plan on buying from them, please use our affiliate link: https://www.trainz.com/MMOP You can also use our unique promo code: MMOP for $10 off a single purchase on the Trainz.com website   Show Notes and Links: Gizmo Trains: https://www.youtube.com/@gizmotrains Miniature Models Facebook Page: https://www.facebook.com/MattandMattTrainsPodcast Miniature Models YouTube Page: https://www.youtube.com/channel/UCgNPmchzgQJ5SWGQ1eAC58g/featured   Miniature Models Podcast Merchandise https://www.redbubble.com/people/MandM-Podcast/shop   Where you can find the Hosts: Matt R YouTube: https://www.youtube.com/channel/UCjSpNlduCj_M_3tHotCzvZA/videos Facebook: https://www.facebook.com/westchicagorailroad Instagram: https://www.instagram.com/wc_model_railroad/ Matt Z YouTube: https://www.youtube.com/user/trainlover9943/videos Facebook: https://www.facebook.com/trainlover9943 Instagram: https://www.instagram.com/matts.hobbies/ Johnny YouTube: https://www.youtube.com/channel/UCnn81L0rizbm7ZW_znZvTag Facebook: https://www.facebook.com/profile.php?id=100075521222163 Instagram: https://www.instagram.com/audamus_trains/ John Schwartz (RetroMikado) YouTube: https://youtube.com/@RetroMikado?si=znR_Uzm6IpyFUheB Instagram: https://www.instagram.com/retromikado96/   Where you can find the Guests:   Eric Siegel & Lisa (Eric's Trains) YouTube: https://www.youtube.com/user/esiegel76 Website: https://www.ericstrains.com Webcams: https://www.ericstrains.com/webcam/ Twitter: https://twitter.com/ericstrains   Music: Good Vibe by Twisterium from Pixabay  

In this episode of our podcast, we delve into the intricate world of machine learning (ML) deployment with Dr. Eric Siegel, author of the book AI Playbook, Mastering the Rare Art of Machine Learning Deployment. Dr. Siegel, once an avid advocate of ML, now approaches the field with a disciplined yet optimistic perspective. He shares invaluable insights on how businesses can effectively implement ML strategies. Our discussion revolves around a range of compelling topics, from the inspiring story of Jack from UPS, who leveraged his psychology background to revolutionize parcel delivery, to the common pitfalls that cause many ML projects to fail. Eric elucidates the six crucial steps for ML deployment, emphasizing the importance of ethical considerations in this rapidly evolving field. Whether you're a student, a business leader, or just an AI enthusiast, this episode offers a treasure trove of knowledge and strategies to navigate the complex landscape of machine learning deployment. 

We all know that AI will change everything, but it won't really change everything, at least not all at once. That said, big changes are underway right now, and the rate of change will likely continue. What's a savvy business person to do? Check out this episode of DM Radio to find out! Host @eric_kavanagh will interview Dr. Eric Siegel, author of a new book; and Paul Marca of Ikigai Academy. They'll discuss what to expect from AI, and especially how that will affect the workforce.

"There's a gap between the technical side and the business side. You need to bridge that gap with a common understanding of what's predicted, how well, and what's done about it."  – Eric Siegel In this insightful Data Chats episode, we explore the critical intersection of business and machine learning with Eric Siegel, a renowned expert in the field. Eric's insights offer a roadmap for organizations seeking to leverage the power of AI to drive their business forward. Eric Siegel is the founder of Machine Learning Week, former Columbia professor, and bestselling author of his new release, “The AI Playbook: Mastering the Rare Art of Machine Learning Deployment.” He has a talent for bridging the gap between complex data science concepts and the practical application of machine learning in the business world.  Check out Eric's new release, “The AI Playbook: Mastering the Rare Art of Machine Learning Deployment” here.  With his remarkable insights, Eric Siegel sits down with host, Chris Richardson, as he guides us through the exciting yet challenging landscape of AI's role in business. They discuss:  Aligning with Business Objectives: Success comes from defining clear goals and understanding how AI can contribute to achieving them. Measuring Deployment Success: Companies must define meaningful metrics that reflect the project's impact on the business. Human Involvement: While AI and ML hold great potential, there's still a need for human involvement to validate AI-generated results and maintain quality control. New Roles and Responsibilities: As AI's role in business continues to evolve, new job titles and roles, such as machine learning business liaisons, are emerging.  Want to learn more from Eric? Tune in to his previous interview with us here.  Drive Business Growth Through Data Science As you reflect on the importance of seamless collaboration between business development and data science, take the first step toward ensuring your organization thrives in the era of data-driven decision-making with The Pragmatic Institute Data Maturity Assessment.  The assessment is designed for organizations looking to measure and grow their level of data maturity, helping them identify pillars for improvement and best practices to make the most out of the data at hand. It's not just a tool; it's your gateway to unlocking your business's potential through data-driven strategies.  Take the Assessment

In this episode of Mining Your Own Business, Evan Wimpey chats with Eric Siegel, bestselling author and founder of Machine Learning Week. Tune in as he shares why businesses need to focus on machine learning projects that work in the real world. Eric also dives into the importance of measuring the impact of machine learning projects, the need for business professionals to understand the technology, and the potential challenges associated with overhyped AI expectations. In this episode you will learn: 

In our kickoff to Season 8 of Trending in Ed, host Mike Palmer welcomes Melissa Griffith and Dan Strafford back to the show to discuss the 2023 Gartner Hype Cycle for Emerging Technologies. We reflect on how the hype cycle framework can be applied to understand the trajectory of any new technology or cultural phenomenon. We debate whether the current hype around AI will lead to an "AI winter" as expectations aren't met, or if investment and development will power through any disillusionment based in part on Eric Siegel's HBR article on the topic. We explore how individuals can take advantage of new AI tools for enhanced productivity, while also acknowledging concerns around impacts on human creativity and labor.   For education, we consider how to best teach students ethical, appropriate uses of AI as a supplemental tool rather than a crutch. We emphasize the need for continual learning and adaptability in our current era of rapid technological change. Overall, we share some cautious optimism about riding out the "AI fog" to emerge with productivity-enhancing applications. Don't miss it! Subscribe to Trending in Education wherever you listen to podcasts. Visit us at TrendinginEd.com for more sharp takes on what's emerging in learning and beyond.

Podcast questions and inquiries? Email us: mattandmattoscaletrains@gmail.com New URL for the Podcast: www.mandmpodcast.com Please note: The primary purpose of this Podcast is to educate. We do not constitute advice or services. Please seek advice from an appropriate legal professional in your state, county, or city.   Join Matt R, Matt Z, Ryan Kunkle (Lionel), Eric Siegel, Meghan Fraser (Lionel) and Corey Harwell (Lionel) as we dive into the Lionel 2023 V2 catalog.   Discord Server Link: https://discord.gg/5rpxw8F4DY Please note that you will need to read the rules and click a box to verify that you understand them before you're able to join the server. We want this community to be a welcoming and respectful place.   This Podcast is now available on Spotify and Amazon Music / Audible. We are also available from our usual sources like Apple Podcasts, Google Podcasts, and YouTube.   Spotify: https://open.spotify.com/show/0OOWgO2vvI38ZFOtF4BxkU?si=2a853e2b36a44f80 Google Podcasts: https://bit.ly/3FzsisW Apple Podcasts: https://podcasts.apple.com/us/podcast/the-matt-and-matt-o-scale-trains-podcast/id1527505788 Amazon Music: https://music.amazon.com/podcasts/f8fe369d-985c-4d14-af1f-dc4abf112b06/the-matt-and-matt-o-scale-trains-podcast   The Matt and Matt O-Scale Trains Podcast is now part of the Trainz partner program. If you do plan on buying from them, please use our affiliate link: https://www.trainz.com/MMOP You can also use our unique promo code: MMOP for $10 off a single purchase on the Trainz.com website   Show Notes and Links: Matt and Matt Facebook Page: https://www.facebook.com/MattandMattTrainsPodcast Matt and Matt YouTube Page: https://www.youtube.com/channel/UCgNPmchzgQJ5SWGQ1eAC58g/featured   Matt and Matt Podcast Merchandise Matt and Matt Merchandise: https://www.redbubble.com/people/MandM-Podcast/shop   Where you can find the Hosts: Matt R YouTube: https://www.youtube.com/channel/UCjSpNlduCj_M_3tHotCzvZA/videos Facebook: https://www.facebook.com/westchicagorailroad Instagram: https://www.instagram.com/wc_model_railroad/ Matt Z YouTube: https://www.youtube.com/user/trainlover9943/videos Facebook: https://www.facebook.com/trainlover9943 Instagram: https://www.instagram.com/matts.hobbies/ Johnny YouTube: https://www.youtube.com/channel/UCnn81L0rizbm7ZW_znZvTag Facebook: https://www.facebook.com/profile.php?id=100075521222163 Instagram: https://www.instagram.com/audamus_trains/   Where you can find the Guests: Ryan Kunkle (Lionel), Meghan Fraser (Lionel), Corey Harwell (Lionel) YouTube: https://www.youtube.com/user/LionelModelTrains/videos Facebook: https://www.facebook.com/LionelModelTrains Instagram: https://www.instagram.com/lionel_trains/ Website: http://www.lionel.com   Eric Siegel (Eric's Trains) YouTube: https://www.youtube.com/user/esiegel76 Website: https://www.ericstrains.com Webcams: https://www.ericstrains.com/webcam/ Twitter: https://twitter.com/ericstrains   Music: Good Vibe by Twisterium from Pixabay  

Eric Siegel is a leading consultant and former Columbia University professor. He is the founder of the popular Predictive Analytics World and Deep Learning World conference series.  In this episode, Eric shares his decades of experience in predictive analytics. He discusses why ML is useful, and how predictive analytics have been used in business. Eric shares his view on prescriptive analytics, AI, and also explains uplift-modelling concepts, and why it is hard and so powerful.  Eric's RecommendationsBooks:Competing on Analytics: Updated with a New Introduction, The New Science of Winning by Thomas H. Davenport, Jeanne G. Harris, 2017Applied Predictive Analytics: Principles and Techniques for the Professional Data Analyst, by Dean Abbot Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel Papers: Sculley, David, Gary Holt, Daniel Golovin, Eugene Davydov, Todd Phillips, Dietmar Ebner, Vinay Chaudhary, Michael Young, Jean-Francois Crespo, and Dan Dennison. "Hidden technical debt in machine learning systems." Advances in neural information processing systems 28 (2015). Elder IV, John F. "The generalization paradox of ensembles." Journal of Computational and Graphical Statistics 12, no. 4 (2003): 853-864. 

In the early twentieth century, Evangeline Adams was the most famous fortune teller in America. Kings, actors and even bankers came to her for predictions. Though Adams was an astrologer, she wasn't the only one predicting the future at the time. Government agencies started making predictions about the weather. As the years went by, science fiction writers and scientists predicted space travel, wind farms, hormone replacement therapy and more.Today, we're trying to predict the future of buyer behavior, the Earth's climate and health outcomes. But instead of relying on the stars, researchers use predictive models and deep learning algorithms. From the fate of our planet to what an individual will buy online to what crimes will occur next week, there's almost no limit to the questions many are trying to answer using artificial intelligence. Hear what's in the cards for predictions on this episode of Trailblazers.Featuring Jamie Pietruska, Bill Behrens, Eric Siegel, Aaron Andalman, Ben Reis and Ishanu Chattopadhyay.For more on the podcast go to delltechnologies.com/trailblazers

Podcast questions and inquiries? Email us: mattandmattoscaletrains@gmail.com New URL for the Podcast: www.mandmpodcast.com Please note: The primary purpose of this Podcast is to educate. We do not constitute advice or services. Please seek advice from an appropriate legal professional in your state, county, or city.   Join Matt R, Johnny, Ryan Kunkle from Lionel, Eric Siegel, and Chris M as we dive into the Lionel 2023 V1 catalog.   Discord Server Link: https://discord.gg/5rpxw8F4DY Please note that you will need to read the rules and click a box to verify that you understand them before you're able to join the server. We want this community to be a welcoming and respectful place.   This Podcast is now available on Spotify and Amazon Music / Audible. We are also available from our usual sources like Apple Podcasts, Google Podcasts, and YouTube.   Spotify: https://open.spotify.com/show/0OOWgO2vvI38ZFOtF4BxkU?si=2a853e2b36a44f80 Google Podcasts: https://bit.ly/3FzsisW Apple Podcasts: https://podcasts.apple.com/us/podcast/the-matt-and-matt-o-scale-trains-podcast/id1527505788 Amazon Music: https://music.amazon.com/podcasts/f8fe369d-985c-4d14-af1f-dc4abf112b06/the-matt-and-matt-o-scale-trains-podcast   The Matt and Matt O-Scale Trains Podcast is now part of the Trainz partner program. If you do plan on buying from them, please use our affiliate link: https://www.trainz.com/MMOP You can also use our unique promo code: MMOP for $10 off a single purchase on the Trainz.com website   Show Notes and Links: Matt and Matt Facebook Page: https://www.facebook.com/MattandMattTrainsPodcast Matt and Matt YouTube Page: https://www.youtube.com/channel/UCgNPmchzgQJ5SWGQ1eAC58g/featured   Matt and Matt Podcast Merchandise Matt and Matt Merchandise: https://www.redbubble.com/people/MandM-Podcast/shop   Where you can find the Hosts: Matt R YouTube: https://www.youtube.com/channel/UCjSpNlduCj_M_3tHotCzvZA/videos Facebook: https://www.facebook.com/westchicagorailroad Instagram: https://www.instagram.com/wc_model_railroad/ Matt Z YouTube: https://www.youtube.com/user/trainlover9943/videos Facebook: https://www.facebook.com/trainlover9943 Instagram: https://www.instagram.com/matts.hobbies/ Johnny YouTube: https://www.youtube.com/channel/UCnn81L0rizbm7ZW_znZvTag Facebook: https://www.facebook.com/profile.php?id=100075521222163 Instagram: https://www.instagram.com/audamus_trains/   Where you can find the Guests:   Ryan Kunkle (Lionel) YouTube: https://www.youtube.com/user/LionelModelTrains/videos Facebook: https://www.facebook.com/LionelModelTrains Instagram: https://www.instagram.com/lionel_trains/ Website: http://www.lionel.com Eric Siegel (Eric's Trains) YouTube: https://www.youtube.com/user/esiegel76 Website: https://www.ericstrains.com Webcams: https://www.ericstrains.com/webcam/ Twitter: https://twitter.com/ericstrains Chris M (Chris's Trains and Things) YouTube: Chris's Trains and Things Instagram: https://www.instagram.com/chrismontrains/   Music: Good Vibe by Twisterium from Pixabay  

“Even if you don't drink one bit of the A.I. Kool-Aid and you're a senior expert practitioner in machine learning, when you're trying to start a new initiative at your corporation, you're still very liable to make this extremely prevalent mistake that leads to a lack of deployment. And the mistake is that we all, on some level, are fetishizing the technology.” -      Eric Siegel   In this episode of Data Chats, Chris Richardson interviews Eric Siegel, Ph.D., leading consultant and former Columbia University professor who makes machine learning understandable and captivating. He is also the founder of the Predictive Analytics World and Deep Learning World conference series, which has served more than 17,000 attendees since 2009.They discuss: How to use A.I. to improve your organization's capabilities and performance Common mistakes business leaders make with understanding machine learning Why top data scientists fail to make successful models most of the time How operational changes lead to improved data analysis What separates a great organization from the rest when it comes to predictive analytics Necessity of socialization and buy-in to successfully implement predictive analysis  Ethical implications and risks of machine learning Continue Learning | Data Science for Business Leaders Data Science for Business Leaders shows you how to partner with data professionals to uncover business value, make informed decisions and solve problems. Learn More

Podcast questions and inquiries? Email us: mattandmattoscaletrains@gmail.com New URL for the Podcast: www.mandmpodcast.com   Join Matt R, Matt Z, Johnny, Ryan Kunkle from Lionel and Eric Siegel as we dive in and review the Lionel 2022 V2 Catalog.   Discord Server Link: https://discord.gg/5rpxw8F4DY Please note that you will need to read the rules, and click a box to verify that you understand them before you're able to join the server. We want this community to be a welcoming and respectful place.   This Podcast is now available on Spotify and Amazon Music / Audible. We are also available from our usual sources like Apple Podcasts, Google Podcasts, and YouTube.   Spotify: https://open.spotify.com/show/0OOWgO2vvI38ZFOtF4BxkU?si=2a853e2b36a44f80 Google Podcasts: https://bit.ly/3FzsisW Apple Podcasts: https://podcasts.apple.com/us/podcast/the-matt-and-matt-o-scale-trains-podcast/id1527505788 Amazon Music: https://music.amazon.com/podcasts/f8fe369d-985c-4d14-af1f-dc4abf112b06/the-matt-and-matt-o-scale-trains-podcast   The Matt and Matt O-Scale Trains Podcast is now part of the Trainz partner program. If you do plan on buying from them please use our affiliate link: https://www.trainz.com/MMOP You can also use our unique promo code: MMOP for $10 off a single purchase on the Trainz.com website   Show Notes and Links: Matt and Matt Facebook Page: https://www.facebook.com/MattandMattTrainsPodcast Matt and Matt YouTube Page: https://www.youtube.com/channel/UCgNPmchzgQJ5SWGQ1eAC58g/featured   Matt and Matt Podcast Merchandise Matt and Matt Merchandise: https://www.redbubble.com/people/MandM-Podcast/shop   Where you can find the Hosts:   Matt R YouTube: https://www.youtube.com/channel/UCjSpNlduCj_M_3tHotCzvZA/videos Facebook: https://www.facebook.com/westchicagorailroad Instagram: https://www.instagram.com/wcmrr/ Matt Z YouTube: https://www.youtube.com/user/trainlover9943/videos Facebook: https://www.facebook.com/trainlover9943 Instagram: https://www.instagram.com/matts.hobbies/ Johnny YouTube: https://www.youtube.com/channel/UCnn81L0rizbm7ZW_znZvTag Facebook: https://www.facebook.com/profile.php?id=100075521222163 Instagram: https://www.instagram.com/audamus_trains/   Where you can find the Guests: Ryan Kunkle (Lionel) YouTube: https://www.youtube.com/user/LionelModelTrains/videos Facebook: https://www.facebook.com/LionelModelTrains Instagram: https://www.instagram.com/lionel_trains/ Website: http://www.lionel.com Eric Siegel (Eric's Trains) YouTube: https://www.youtube.com/user/esiegel76 Website: https://www.ericstrains.com Webcams: https://www.ericstrains.com/webcam/ Twitter: https://twitter.com/ericstrains   Music: Good Vibe by Twisterium from Pixabay  

Join Matt R, Matt Z, Johnny, Ryan Kunkle from Lionel and Eric Siegel as we dive into the Lionel 2022 Big Book Catalog.   Lionel 2022 Big Book Catalog Link: http://catalogs.lionel.com/2022/BB/   Discord Server Link: https://discord.gg/5rpxw8F4DY Please note that you will need to read the rules, and click a box to verify that you understand them before you're able to join the server. We want this community to be a welcoming and respectful place.   This Podcast is now available on Spotify and Amazon Music / Audible. We are also available from our usual sources like Apple Podcasts, Google Podcasts, and YouTube.   Spotify: https://open.spotify.com/show/0OOWgO2vvI38ZFOtF4BxkU?si=2a853e2b36a44f80 Google Podcasts: https://bit.ly/3FzsisW Apple Podcasts: https://podcasts.apple.com/us/podcast/the-matt-and-matt-o-scale-trains-podcast/id1527505788 Amazon Music: https://music.amazon.com/podcasts/f8fe369d-985c-4d14-af1f-dc4abf112b06/the-matt-and-matt-o-scale-trains-podcast     Show Notes and Links: Podcast questions and inquiries? Email us: mattandmattoscaletrains@gmail.com Matt and Matt Podcast Facebook Page Matt and Matt Podcast YouTube Page Matt and Matt Official Merchandise Merch Code: MAMPOD - 10% off   Where you can find the Hosts:   Matt R YouTube: West Chicago Model Railroad Facebook: https://www.facebook.com/westchicagorailroad Instagram: https://www.instagram.com/wcmrr/ Matt Z YouTube: Matt-Trainlover9943 Facebook: https://www.facebook.com/trainlover9943 Johnny YouTube: Audamus Instagram: https://www.instagram.com/audamus_trains/   Where you can find the Guests:   Ryan Kunkle (Lionel) YouTube: Lionel Trains Website: http://www.lionel.com Facebook: https://www.facebook.com/LionelModelTrains Eric Siegel YouTube: Eric's Trains Website:  https://www.ericstrains.com Webcams: https://www.ericstrains.com/webcam/ Twitter: https://twitter.com/ericstrains   Music: Midnight City by Mikael Manvelyan  

Dr. Eric Siegel joins the Water Foresight Podcast to discuss "The Multiple Lenses of Predictive Analytics."  What is the difference between "big data," "artificial intelligence," "machine learning," and "predictive analytics"? How will predictive analytics change (and change society) over the next 10 years? Will the application of predictive analytics expand throughout the water sector? Does lift modeling have anything to do with lift stations? What are the ethical implications or risks of predictive analytics? Is there a social justice challenge? Is there a cybersecurity challenge? Are there any current applications of predictive analytics from other sectors likely to make their way into the water sector? Are there emerging Constitutional issues in the future of predictive analytics? What is "deep learning"?  Was this invented by Jack Handy? Finally, will predictive analytics keep slow drivers out of the left-hand lane during rush hour? The podcast is cautiously optimistic.#water #WaterForesight #strategicforesight #foresight #futures @Aqualaurus

Join Matt R and Matt Z as we interview the legendary YouTube model Railroader Eric Siegel from Eric's Trains. This episode is part 2 in a two part podcast interview with Eric Siegel.   Show Notes and Links: Podcast questions and inquiries? Email us: mattandmattoscaletrains@gmail.com Matt and Matt Podcast Facebook Page Matt and Matt Official Merchandise Merch Code: MAMPOD - 10% off   Where you can find Eric Siegel: YouTube: Eric's Trains Website:  https://www.ericstrains.com Webcams: https://www.ericstrains.com/webcam/ Twitter: https://twitter.com/ericstrains Where you can find the Hosts: Matt R YouTube: West Chicago Model Railroad Facebook: https://www.facebook.com/westchicagorailroad Instagram: https://www.instagram.com/wcmrr/ Matt Z YouTube: Matt-Trainlover9943 Facebook: https://www.facebook.com/trainlover9943   Music: Queen - Don't Stop Me Now  

Join Matt R and Matt Z as we interview the legendary YouTube model Railroader Eric Siegel from Eric's Trains. This episode is part 1 in a two part podcast interview with Eric Siegel.   Show Notes and Links: Podcast questions and inquiries? Email us: mattandmattoscaletrains@gmail.com Matt and Matt Podcast Facebook Page Matt and Matt Official Merchandise Merch Code: MAMPOD - 10% off   Where you can find Eric Siegel: YouTube: Eric's Trains Website:  https://www.ericstrains.com Webcams: https://www.ericstrains.com/webcam/ Twitter: https://twitter.com/ericstrains Where you can find the Hosts: Matt R YouTube: West Chicago Model Railroad Facebook: https://www.facebook.com/westchicagorailroad Instagram: https://www.instagram.com/wcmrr/ Matt Z YouTube: Matt-Trainlover9943 Facebook: https://www.facebook.com/trainlover9943   Music: Queen - Don't Stop Me Now  

1-30-21 Dr. Eric Siegel by Bob and Stacey

Today on the news, we jump right into our Weekly News Reel, where we hear from local newspaper reporters about their latest stories in our region. Concerns over water supply are leading Moab City to create water restriction ordinances. Editor Doug McMurdo at The Times-Independent tells us more about their coverage of this issue, as well as the latest on the local fish refuge, and a new transient room tax reform bill. And (10:00), Grand County recently passed an ordinance clarifying that camping on private property outside of an established campground is illegal. Moab Sun News editor Maggie McGuire discusses its implications for marginalized locals, as well as a controversial highway that could impact desert tortoise habitat in southern Utah. Plus (19:00), our partners at KVNF speak with Eric Siegel from High Country News, who’s latest article profiles rural queerness in the West. Show Notes: Photo: Luna Anna Archey/High Country News KVNF: Local Motion – The Latest From High Country News https://www.kvnf.org/post/local-motion-latest-high-country-news#stream/0 Weekly News Reel Mentions – The Times Independent Water restrictions coming to Moab https://www.moabtimes.com/articles/water-restrictions-coming-to-moab/ Final phase of wetlands project well underway https://www.moabtimes.com/articles/final-phase-of-wetlands-project-well-underway/ Albrecht sponsors TRT reform bill https://www.moabtimes.com/articles/albrecht-sponsors-trt-reform-bill/ Moab Sun News What we mean when we say ‘camping’ https://www.moabsunnews.com/news/article_1e05e968-619b-11eb-b471-3727d49ae0ec.html Controversial highway offers protections for climbing area https://www.moabsunnews.com/news/article_b56876ea-619b-11eb-bf71-5f5c57d2aaf7.html High Country News Meet the gun-toting ‘Tenacious Unicorns’ in rural Colorado https://www.hcn.org/issues/53.2/south-communities-meet-the-gun-toting-tenacious-unicorns-in-rural-colorado?fbclid=IwAR3bJnVWO3zFJc24dEyLoeztG4j9e2B0dTl6eK8WV2YwK3jmO-mU5O2rPiw

12-5-20 Dr. Eric Siegel by Bob and Stacey

Robert Ramirez and Nick Paul chat with Eric Seigel about stealing, call backs, Second City, revealing methods, illusions, social media magicians, his instagram character @ericisthirstin / TikTok... "Two Magicians. One Mic." is a podcast designed by working magicians for magicians and performers. Inspired by podcasts such as WTF and Nerdist, we dissect magic and observe it from the performance perspective. Come listen as we interview working magicians and analyze the performance community.

IBF on Demand sponsored by Arkieva. Learn about Swiftcast, Machine Learning Enabled Demand Forecasting from Arkieva: http://bit.ly/swifcastIBF's industry-leading S&OP Assessments assess your company's maturity level and provide tailor-made recommendations to improve specific areas - all designed to take you to the next level in your S&OP evolution. Click here for more information: https://bit.ly/3d58dMTWhat is predictive analytics and how does it work? I bring in Eric Siegel to help answer that question because two Eric's are better than one! He is author of the bestseller, 'Predictive Analytics, The Power To Predict Who Will Click, Buy Lie Or Die', former Columbia University professor, founder of Predictive Analytics World, and rapper (seriously!). Demand planning will become the home of predictive analytics, so let's get ready for it now.05:00 What is predictive analytics?06:00 The overlap between forecasting and predictive analytics.07:13 Why are predictive and analytics revolutionizing business? 09:20 Is predictive analytics as complicated as it sounds?11:30 How machine learning works.13:25 Logistic regression.15:33 Big Data and training data.15:58 Finding the right predictive model.20:20 Ensemble models and the wisdom of averages.23:10 Uplift modeling/persuasion modeling to create the future.27:15 How to gain knowledge in predictive analytics.33:00 My new book on predictive analytics (coming soon!).34:35 Arkieva's Swiftcast.

5-9-20 Dr. Eric Siegel by Bob and Stacey

Eric Siegel, Ph.D. is founder of the Predictive Analytics World and Deep Learning World conference series, executive editor of “The Predictive Analytics Times,” and author of “Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die.” A former Columbia University professor and host of the Dr. Data Show web series, Siegel is a renowned speaker and educator who has been commissioned for more than 100 keynote addresses across multiple industries. Eric is best known for making the “how” and “why” of predictive analytics (aka machine learning) understandable and captivating to his audiences. In our chat, we covered: The value of defining business outcomes and end user’s needs prior to starting the technical work of predictive modeling, algorithms, or software design. The idea of data prototypes being used before engaging in data science to determine where models could potentially fail—saving time while improving your odds of success. The first and most important step of Eric’s five-step analytics deployment plan Getting multiple people aligned and coordinated about pragmatic considerations and practical constraints surrounding ML project deployment. The score (1-10) Eric  gave the data community on its ability to turn data into value The difference between decision support and decision automation and what the Central Intelligence Agency’s CDAO thinks about these two methods for using machine learning. Understanding how human decisions are informed by quantitative predictions from predictive modes, and what’s required to deliver information in a way that aligns with their needs. How Eric likes to bring agility to machine learning by deploying and scaling models incrementally to mitigate risk Where the analytics field currently stands in its overall ability to generate value in the last mile. Resources and Links: Machine Learning Week #experiencingdata PredictiveAnalyticsWorld.com ThePredictionBook.com Dr. Data Show Twitter: @predictanalytic Quotes from Today’s Episode “The greatest pitfall that hinders analytics is not to properly plan for its deployment.” — Brian, quoting Eric “You don’t jump to number crunching. You start [by asking], ‘Hey, how is this thing going to actually improve business?’ “ — Eric “You can do some preliminary number crunching, but don’t greenlight, trigger, and go ahead with the whole machine learning project until you’ve planned accordingly, and iterated. It’s a collaborative effort to design, target, define scope, and ultimately greenlight and execute on a full-scale machine learning project.” — Eric “If you’re listening to this interview, it’s your responsibility.” — Eric, commenting on whose job it is to define the business objective of a project. “Yeah, so in terms of if 10 were the highest potential [score], in the sort of ideal world where it was really being used to its fullest potential, I don’t know, I guess I would give us a score of [listen to find out!]. Is that what Tom [Davenport] gave!?” — Eric, when asked to rate the analytics community on its ability to deliver value with data “We really need to get past our outputs, and the things that we make, the artifacts and those types of software, whatever it may be, and really

“It is an extremely powerful technology that helps us automate mass scale decisions. It's sort of the implementation of private and public policies and automation and mechanization of those societal functions. It brings up a lot of ethical issues around social justice and how this affects all the people about whom decisions are being made., says Eric Seigel in episode 15 of the Career Nation ShowHere are some of the highlights from this episode:Why the term AI is misleading?What is predictive analytics? How does it work?How it generates a predictive model?The operationalization of the model.The opportunities with machine learning and predictive analyticsYou can get the copy of Eric Seigel’s best selling book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, from here: https://www.amazon.in/Predictive-Analytics-Power-Predict-Click-ebook/dp/B019HR9X4U

1-11-20 Dr. Eric Siegel by Bob and Stacey

My guest today is Eric Siegel, a software developer, and Consciousness explorer who had a spontaneous Kundalini awakening before he even knew what the word Kundalini meant. He’s part of the millennial generation and has only been meditating for about 15 years. Apart from being a very intelligent, normal and well-adapted young man, he maintains a very serious and well-disciplined spiritual life while working in the world and holding a regular job. My interest in interviewing him emerged from extensive conversations we have had over the years about his meditation and specifically his experience integrating an active Kundalini into his otherwise very normal life. While I don’t normally interview people this young, meditators with varying levels of expertise from beginners to advanced will find our conversation interesting, edifying and I believe very uplifting. The early part of the conversation is just a warmup for the deeper and more detailed discussion in the later parts of the episode. We talk about the subtle energies of breath and mantra, the Sufi tradition and parallels with Judaism and the mystical teachings in the Old Testament. He shares his early discovery of Kundalini after being unwittingly and unexpectedly awakened and how he dealt with it on a daily basis for months until finally finding some answers to what was happening to him in a detailed book by a well-known Kundalini master, Baba Muktananda. In our far-ranging conversation, we cover the importance of diet and lifestyle including sleep in the nurturing and efficient development of Kundalini’s potential. The whole conversation is practice-oriented and most will find it very informative and enlightening. I hope you enjoy this conversation with Eric that was recorded at my dining room table. To directly contact our hosts, visit their respective websites:https://www.meditatenow.net/ - Show Notes, Links and Resources, including Glossary of Terms for all Episodes and to contact Marc directly. https://larryholmespracticalwisdom.com/ - For All Episodes and to contact Larry directly and review his consulting and coaching services.

Eric Siegel, PhD, discusses his book Predictive Analytics and how to use data to predict who will click, buy, lie or die. Eric is a former Columbia University professor and you’ve seen him in places like Bloomberg TV, NPR and Fox News, among others. Get the the insight to predict the disruptors and drivers of business today. Want to be a guest? DigitalTransformationPodcast.net/guest Want to be a sponsor? DigitalTransformationPodcast.net/sponsor

3-2-19 Dr. Eric Siegel by Bob and Stacey

In episode 187 of the Get Published Podcast, Host and 13-Time Bestselling Author Paul G. Brodie interviews Eric Siegel about his author journey and the importance of ad placement on amazon.

8-11-18 Dr. Eric Siegel by Bob and Stacey

Interview with Daniel Donohue and Eric Siegel (The New Bad Boys of Magic) In this episode, we chat with Daniel and Eric aka The New Bad Boys of Magic! We talk about how they met, how they got into magic, the dating app they will make, their new show (Dirty Tricks), and so much more! […] The post Episode 72 – Interview with Daniel Donohue and Eric Siegel (The New Bad Boys of Magic) appeared first on My Haunt Life.

1-27-18 Dr. Eric Siegel by Bob and Stacey

Most of us know by now that recreational cannabis became legal in California on Jan. 1. But there's still a lot we don't know about the plant, despite its long history of human use, says Eric Siegel, the director of the UC Botanical Garden. So the garden is hosting a lecture series called the "Science of Cannabis," where experts will discuss everything from the environmental impacts of large-scale cannabis cultivation to the neurological effect of cannabis in our brains.Read more about the lecture series on Berkeley News. See acast.com/privacy for privacy and opt-out information.

Legendary singer/composer Charles Wright’s mega-hit song “Express Yourself” has been chosen to provide the thematic thrust for what promises to be the breakout animation movie of 2017 Legendary singer/composer Charles Wright’s mega-hit song “Express Yourself” has been chosen to provide the thematic thrust for what promises to be the breakout animation movie of 2017 (August), a 3-D computer-animated summer release entitled The Emoji Movie. This state-of-the-art film is a Sony Pictures Animation, and it brings to life the images used by nearly everyone in online messaging today. The movie’s hilarious screenplay is based on the story by Eric Siegel and Tony Leondis. Leondis also directs the film, and Michelle Raimo Kouyate is its producer. At the 2016 CinemaCon (a meeting of theater owners), it was announced that The Emoji Movie would be set in the digital world — in a smartphone. Very smart! The film’s eclectic cast includes T.J. Miller,Ilana Glazer, and James Corden. And, oh yes! Originally entitled Emoji Movie: Express Yourself, the name was changed to The Emoji Movie only weeks ago. “Express Yourself,” a smash hit in the 1970s and perhaps the most familiar commercial tune today, was composed and produced by world-famous musician, composer, and entrepreneur Charles Wright. The tune was selected because of its enormous success and decades-long airing in endless television commercials, including the iPad, and on sensational movie soundtracks. Interestingly, a great theme song in a trailer and a movie can do wonders in generating subtle interest in a film. When you witness this movie in August, notice how the storyline and Wright’s undulating vocals dovetail to an inseparable union

Predictive Analytics World founder Eric Siegel on how data science could determine the 2016 election. Doug Wiens at Washington University shares his work discovering a giant rift underneath the American Midwest. Scott M. Peterson of Peterson Wealth Advisors describes how to make good financial decisions during retirement. Male Survivor board member Chris Anderson on why abuse survivors keep quiet so long. Urologist at Michigan State University David Wartinger on how roller coasters help pass kidney stones.

Fractional CMO, Digital Marketing Strategist, and Leadership Keynote Speaker Michele Price brings you weekly access to the top minds to Master the Inner and Outer Game of business.  Breakthrough Radio is a global business radio show that delivers high impact & pioneering knowledge for leaders in business. Entrepreneurs, startups, sales/marketing/IT professionals join us every Monday. Eric Siegel, author Predictive Analytics and founder of Predictive Analytics World Michele Price, your fractional CMO delivers the Breakthrough Tips segment on "Mastering the Art of Execution". Yared Akalou, co-founder Opening.Co delivers the Breakthrough Byte segment on #FutureofWorkforce. Follow us & ask your questions via twitter using #BBSradio.  You are invited to visit radio show blog at www.TheBreakthroughRadio.com

"Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die" by Eric Siegel Click here to view the show notes! https://www.salesartillery.com/marketing-book-podcast/predictive-analytics-eric-siegel

Fractional CMO, Digital Marketing Strategist, and Leadership Keynote Speaker Michele Price brings you weekly access to the top minds to Master the Inner and Outer Game of business.  Breakthrough Radio is a global business radio show that delivers high impact & pioneering knowledge for leaders in business. Entrepreneurs, startups, sales/marketing/IT professionals join us every Monday. Eric Siegel, author Predictive Analytics and founder of Predictive Analytics World Michele Price, your fractional CMO delivers the Breakthrough Tips segment on "Mastering the Art of Execution". Yared Akalou, co-founder Opening.Co delivers the Breakthrough Byte segment on #FutureofWorkforce. Follow us & ask your questions via twitter using #BBSradio.  You are invited to visit radio show blog at www.TheBreakthroughRadio.com

Dr. Courtney Campbell, host of Pet Talk joins the Steven Maggi Show to talk about answers all of your pet questions from health to grooming to behavior issues for your furry, feathered, or scaled... Experience the excitement and energy of Las Vegas each weekend on VEGAS NEVER SLEEPS with Steven Maggi.

Eric Siegel takes a deeper look at what Predictive Analytics really is and how businesses can use it to make important decisions and improve success.The post #MarketingNerds: Eric Siegel Goes In-Depth on Predictive Analytics appeared first on Search Engine Journal.

Episode 47 - Eric Siegel, PhD, discusses his book Predictive Analytics and how to predict who will click, buy, lie or die. Eric is a former Columbia University professor and you’ve seen him in places like Bloomberg TV, NPR and Fox News, among others. Get the the insight to predict the disruptors and drivers of business today. Host, Kevin Craine   @Everyday_MBA

Join Dr. Carlos as he explores whether analytics can predict who lies, what they buy, and even dies. What are companies predicting about me as a customer?Here are just a few examples:Microsoft helped develop technology that, based on GPS data, accurately predicts one's location up to multiple years beforehand.Target predicts customer pregnancy from shopping behavior, thus identifying prospects to contact with offers related to the needs of a newborn's parents.Tesco (UK) annually issues 100 million personalized coupons at grocery cash registers across 13 countries. Predictive analytics increased redemption rates by a factor of 3.6.Netflix sponsored a $1 million competition to predict which movies you will like in order to improve movie recommendations.One top-five U.S. health insurance company predicts the likelihood an elderly insurance policy holder will die within 18 months in order to trigger end-of-life counseling.Con Edison predicts energy distribution cable failure, updating risk levels that are displayed on operators' screens three times an hour in New York City.ERIC SIEGEL, PhD, founder of Predictive Analytics World and Executive Editor of the Predictive Analytics Times, makes the how and why of predictive analytics understandable and captivating. Eric is a former Columbia University professorwho used to sing educational songs to his studentsand a renowned speaker, educator, and leader in the field.

Notch 6 Episode 52- Eric Siegel of Ericstrains.com stops by to chat about his incredibly successful Youtube channel and website dedicated to O gauge trains. Eric has been instrumental in introducing many new people into the hobby through his O gauge product reviews, scenery tutorials, and more. We'll also discuss his wonderful layout, and some of his favorite products from the last year.  

Eric Siegel, author of "Predictive Analytics," talks with Overdrive Editor Max Heine about the ethics of predictive modeling and its safety and human resources applications for trucking.

Looking for a crystal ball to help you predict what 2014 may bring for your business, your industry, your marketplace? We've got the next best thing – dozens of expert insights into the technologies, strategies, and trends that can help you grow and compete better this year and beyond. These thought leaders will appear on SAP Game-Changers Radio 2014 Predictions – Part 3 LIVE: Todd Wilms, SAP; Michael Denis, Flatirons Solutions; Neal Schact, CommuniTech; Nicolette Van Exel, SAP; Kathy-Ann Hutson, IBM; Padman Ramankutty, Intrigo; Steve Hilton, MachNation; Bill Newman, Newport Consulting; China Gorman, Great Place to Work; Steve Player, Beyond Budgeting Round Table; Jorge Garcia, TEC; Dennis Goodhart, IP Network Consulting; Marcus Baur, Sailing Team Germany; Eric Siegel, Predictive Analytics World; Tim Minahan, SAP. To hear the first two parts of our 2014 Predictions special, visist: http://bit.ly/Predictions2014A and http://bit.ly/Predictions2014B. Wishing you a positively game-changing New Year!

Looking for a crystal ball to help you predict what 2014 may bring for your business, your industry, your marketplace? We've got the next best thing – dozens of expert insights into the technologies, strategies, and trends that can help you grow and compete better this year and beyond. These thought leaders will appear on SAP Game-Changers Radio 2014 Predictions – Part 3 LIVE: Todd Wilms, SAP; Michael Denis, Flatirons Solutions; Neal Schact, CommuniTech; Nicolette Van Exel, SAP; Kathy-Ann Hutson, IBM; Padman Ramankutty, Intrigo; Steve Hilton, MachNation; Bill Newman, Newport Consulting; China Gorman, Great Place to Work; Steve Player, Beyond Budgeting Round Table; Jorge Garcia, TEC; Dennis Goodhart, IP Network Consulting; Marcus Baur, Sailing Team Germany; Eric Siegel, Predictive Analytics World; Tim Minahan, SAP. To hear the first two parts of our 2014 Predictions special, visist: http://bit.ly/Predictions2014A and http://bit.ly/Predictions2014B. Wishing you a positively game-changing New Year!

Today's buzz: Predictive. IBM's Watson beat Mensa on Jeopardy. Target knows your family. Match.com picks mates. How are they so smart? The experts speak. John Elder, Elder Research: “Humans and machines have very different strengths and weaknesses. The best decisions come from combining their two types of wisdom. Greta Roberts, Talent Analytics: “When a predictive approach is added to the hiring process, cost-benefit models sometimes show it is more powerful to screen out potential bottom-performing hires.” Eric Siegel, “Predictive Analytics”: “Everyone's heard that correlation does not entail causality. But without establishing any causality, how can we trust a predictive model?” Henner Schliebs, SAP: “Are CFOs the better CEOs? Advanced finance analytics drive the strategic role of finance heads with holistic intelligence about financial, operational and company performance. Master your margins – become a king.” The New CFO Agenda: Tying Predictive to Financial Performance–Part 2.

Today's buzz: Predictive. IBM's Watson beat Mensa on Jeopardy. Target knows your family. Match.com picks mates. How are they so smart? The experts speak. John Elder, Elder Research: “Humans and machines have very different strengths and weaknesses. The best decisions come from combining their two types of wisdom. Greta Roberts, Talent Analytics: “When a predictive approach is added to the hiring process, cost-benefit models sometimes show it is more powerful to screen out potential bottom-performing hires.” Eric Siegel, “Predictive Analytics”: “Everyone's heard that correlation does not entail causality. But without establishing any causality, how can we trust a predictive model?” Henner Schliebs, SAP: “Are CFOs the better CEOs? Advanced finance analytics drive the strategic role of finance heads with holistic intelligence about financial, operational and company performance. Master your margins – become a king.” The New CFO Agenda: Tying Predictive to Financial Performance–Part 2.

33voices interviews Eric Siegel, Ph.D., founder of Predictive Analytics World.

Over a round of astrophysics mini-golf, learn what goes into creating a world-class science exhibit from Eric Siegel, Director of the NY Hall of Science, Lee Skolnick, the course's architect, and physicist Alan Friedman.