Podcasts about data skeptic

We celebrate episode 1000000000 with some Q&A from host Kyle Polich.  We boil this episode down to four key questions: 1) How do you find guests 2) What is Data Skeptic all about? 3) What is Kyle all about? 4) What are Kyle's thoughts on AGI?   Thanks to our sponsorsdataannotation.tech/programmers https://www.webai.com/dataskeptic  

Susan Gerbic joins Kyle to review some of the surveys Data Skeptic has launch, draft a new survey about podcast listening habits, and then review the results of that survey. You can see those results at the link below. https://survey.dataskeptic.com/survey/result/1675102237053 Watch the videos Susan mentioned on her Youtube page at the link below. https://www.youtube.com/playlist?list=PL7VAuaQDhPTVaLeI1IcpYph5lH19xA1u4

First we nosh on some interesting tidbits about a long-dead casino magnate, a mysterious fortune teller with a prophecy about rom-coms, and a prematurely dead Simon Cowell. Then Kyle Polich of the Data Skeptic podcast joins us to talk about the Missing 411, a concept pushed by several books and movies produced by David Paulides. What or who are the Missing 411, and how are Bigfoot and UFOs involved? Is there a coherent theory about what's going on, and is it based on actual happenings or fabrications? And how does misunderstanding (or completely ignoring) data analysis come into play?

Increasingly, people get most if not all of the information they consume online. Alongside the web sites, videos, apps, and other destinations, we're consistently served advertisements alongside the organic content we search for or discover. Targetted ads make it possible for you to discover relevant new products you might otherwise not have heard about. Targetting can also open a pandora's box of ethical considerations. Online advertising is a complex network of automated systems. Algorithms controlling algorithms controlling what we see. This season of Data Skeptic will focus on the applications of data science to digital advertising technology. In this first episode in particular, Kyle shares some of his own personal experiences and insights working in pay per click marketing.

Linh Da joins us to explore how image segmentation can be done using k-means clustering.  Image segmentation involves dividing an image into a distinct set of segments.  One such approach is to do this purely on color, in which case, k-means clustering is a good option.  Thanks to our Sponsors:   Visit Weights and Biases mention Data Skeptic when you request a demo! & Nomad Data  In the image below, you can see the k-means clustering segmentation results for the same image with the values of 2, 4, 6, and 8 for k.  

Welcome to our new season, Data Skeptic: k-means clustering.  Each week will feature an interview or discussion related to this classic algorithm, it's use cases, and analysis. This episode is an overview of the topic presented in several segments.

Na nova economia digital, cresce o debate sobre propriedade dos dados. De acordo com as legislações atuais o dado é seu e você define o que fará com ele. Até se remunerar a partir das relações estabelecidas na sua jornada digital, explica Fernando Teles, presidente da Drumwave. Você também pode se beneficiar da riqueza da economia dos dados._____LINKS DO EPISÓDIOO debate “Can we Fix Capitalism?”, entre Gillian Tett e Yanis VaroufakisO livro “On Being a Data Skeptic”, de Cathy O'NeilO livro “Tutela e privacidade na Internet”, de Marcel Leonardi_____FALE CONOSCOEmail: news@theshift.info_____ASSINE A THE SHIFTwww.theshift.info

Time series topics on Data Skeptic predate our current season.  This holiday special collects three popular mini-episodes from the archive that discuss time series topics with a few new comments from Kyle.

This episode is hosted by Kyle Polich of the Data Skeptic podcast. We're glad to welcome Kyle to the Software Daily team. Becoming a contributor to an existing software project can be a daunting task for an engineer. A common convention is to add a README file to your repository to serve as a trailhead The post The Missing Readme with Chris Riccomini and Dmitriy Ryaboy appeared first on Software Engineering Daily.

This episode is hosted by Kyle Polich of the Data Skeptic podcast. We’re glad to welcome Kyle to the Software Daily team. Becoming a contributor to an existing software project can be a daunting task for an engineer. A common convention is to add a README file to your repository to serve as a trailhead The post The Missing Readme with Chris Riccomini and Dmitriy Ryaboy appeared first on Software Engineering Daily.

This episode is hosted by Kyle Polich of the Data Skeptic podcast. We’re glad to welcome Kyle to the Software Daily team. Becoming a contributor to an existing software project can be a daunting task for an engineer. A common convention is to add a README file to your repository to serve as a trailhead The post The Missing Readme with Chris Riccomini and Dmitriy Ryaboy appeared first on Software Engineering Daily.

This episode is hosted by Kyle Polich of the Data Skeptic podcast. We’re glad to welcome Kyle to the Software Daily team. Becoming a contributor to an existing software project can be a daunting task for an engineer. A common convention is to add a README file to your repository to serve as a trailhead

Today on the show Derek Driggs, a PhD Student at the University of Cambridge. He comes on to discuss the work Common Pitfalls and Recommendations for Using Machine Learning to Detect and Prognosticate for COVID-19 Using Chest Radiographs and CT Scans. Help us vote for the next theme of Data Skeptic! Vote here: https://dataskeptic.com/vote

QAnon is a conspiracy theory born in the underbelly of the internet.  While easy to disprove, these cryptic ideas captured the minds of many people and (in part) paved the way to the 2021 storming of the US Capital. This is a contemporary conspiracy which came into existence and grew in a very digital way.  This makes it possible for researchers to study this phenomenon in a way not accessible in previous conspiracy theories of similar popularity. This episode is not so much a debunking of this debunked theory, but rather an exploration of the metadata and origins of this conspiracy. This episode is also the first in our 2021 Pilot Season in which we are going to test out a few formats for Data Skeptic to see what our next season should be.  This is the first installment.  In a few weeks, we're going to ask everyone to vote for their favorite theme for our next season.  

When I think of the trends I’ve seen in data science over the last few years, perhaps the most significant and hardest to ignore has been the increased focus on deployment and productionization of models. Not all companies need models deployed to production, of course but at those that do, there’s increasing pressure on data science teams to deliver software engineering along with machine learning solutions. On that note my guest for today is Aditya Prabhakaron and he is a Senior Data Scientist at Robert Bosch Engineering and Business Solutions. He started his career as a Data Scientist with Rolls – Royce where he was the Technical Lead for the Analytics of entire engine program. I’ve had the opportunity to work closely with him at Bosch especially in the realm of conceptualizing, formulating and driving AI/ML products With a Bachelor’s degree from NIT and a Master’s degree from IIT, he joins us today to share interesting insights, perspectives and his take on Data Science and its future.

Niclas Boehmer, second year PhD student at Berlin Institute of Technology, comes on today to discuss the computational complexity of bribery in elections through the paper “On the Robustness of Winners: Counting Briberies in Elections.” Links Mentioned: https://www.akt.tu-berlin.de/menue/team/boehmer_niclas/ Works Mentioned: “On the Robustness of Winners: Counting Briberies in Elections.” by Niclas Boehmer, Robert Bredereck, Piotr Faliszewski. Rolf Niedermier Thanks to our sponsors: Springboard School of Data: Springboard is a comprehensive end-to-end online data career program. Create a portfolio of projects to spring your career into action. Learn more about how you can be one of twenty $500 scholarship recipients at springboard.com/dataskeptic. This opportunity is exclusive to Data Skeptic listeners. (Enroll with code: DATASK) Nord VPN: Protect your home internet connection with unlimited bandwidth. Data Skeptic Listeners-- take advantage of their Black Friday offer: purchase a 2-year plan, get 4 additional months free. nordvpn.com/dataskeptic (Use coupon code DATASKEPTIC)

Don't miss out on the next WeAreLATech podcast episode, get notified by signing up here http://wearelatech.com/podcastWelcome to WeAreLATech's LA Tech Startup Spotlight!“Everything Data Science"WeAreLATech Podcast is a WeAreTech.fm production.To support our podcast go to http://wearelatech.com/believeTo be featured on the podcast go to http://wearelatech.com/feature-your-la-startup/Want to be featured in the WeAreLATech Community? Create your profile here http://wearelatech.com/communityHost, Espree Devorahttps://twitter.com/EspreeDevoraGuest,Linh Da Tran of Data Skepticlindha@dataskeptic.comFor a calendar of all LA Startup events go to, http://WeAreLATech.comTo further immerse yourself into the LA Tech community go to http://wearelatech.com/vipLinks Mentioned:Data Skeptic, https://dataskeptic.com/Data Skeptic Podcast, https://dataskeptic.com/podcastBusiness.com, https://www.business.com/Dollar Shave Club, https://www.dollarshaveclub.com/Bixel Exchange, http://bixelexchange.com/People Mentioned:Kyle Polich, https://www.linkedin.com/in/kyle-polich-5047193/Cam Kashani, https://twitter.com/camskashaniCredits:Produced and Hosted by Espree Devora, http://espreedevora.comStory produced, Edited and Mastered by Adam Carroll, http://www.ariacreative.ca/Show Notes by Karl Marty, http://karlmarty.comMusic by Jay Huffman, https://soundcloud.com/jayhuffmanShort Title: Data Skeptic

On this episode of The Artists of Data Science, we get a chance to hear from Kyle Polich, a computer scientist turned data skeptic. He has a wide array of interests and skills in A.I, machine learning, and statistics. These skills have made him a sought after consultant in the data science field. He is also the host of the very popular data podcast, Data Skeptic, which discusses topics related to data science all from the perspective of applying critical thinking and the scientific method to evaluate the veracity of claims and efficacy of approaches. In this episode, Kyle defines what a data skeptic is, and also goes on to give advice on how to communicate effectively with leaders and executives as a data scientist. Kyle brings a very unique perspective related to all things data, along with actionable advice! WHAT YOU WILL LEARN [00:11:49] Probabilistic data structures [00:15:19] How probabilitistic data structures will change the future [18:55] Is data science more of an art or science? [23:36] Advice for data scientists trapped in a perfectionist mindset [30:43] Important soft skills that you need to succeed [39:40] How to communicate your ideas with executives QUOTES [11:43] "…greatness is achieved by a commitment to your craft and pursuing it." [16:42] "The greatest trick the devil ever pulled was convincing the world he didn't exist. That's what good data science does to me." [24:42] …"being able to fall down but get up fast is important." FIND KYLE ONLINE LinkedIn:https://www.linkedin.com/in/kyle-polich-5047193/ Twitter:https://twitter.com/DataSkeptic Podcast:https://dataskeptic.com/ SHOW NOTES [00:03:01] How Kyle got into data science [00:05:20] What the heck is a data skeptic? [00:07:47] What do you think the next big thing in data science is going to be the next, say, two to five years. [00:11:04] How to be a great data scientist [00:11:49] Kyle gives us a primer on probabilistic data structures [00:15:19] How do you see probabilistic data structures impacting society in the next two to five years? [00:17:19] Data skeptic mission [00:18:39] Kyle answers the question - how do you view data science? Do you think it's more of the art or more science? [00:21:09] We talk about principles and methodologies as it related to art and science [00:21:52] Kyle shares his thoughts on the creative process in data science [00:23:22] Kyle shares his thoughts on being a perfectionist when you're working on a project [00:25:28] Do you have any tips for people who are coming from a non-technical background and they're coming up to these technical concepts face to face for the first time? [00:26:42] We talk about the importance of being a lifelong learner and Kyle shares some advice for aspiring data scientists out there who feel like they haven't learned enough yet to even consider breaking into the field. [00:28:47] What is your advice for data scientists who they feel like they've learned enough, and just don't even need to learn anything else to be successful? [00:30:27] We talk about the soft-skils that candidates should pick-up, and Kyle shares advice for people who are in their first data science roles. [00:31:03] Some insight into the purpose of your resume and how you should leverage that for your job search [00:34:17] We talk about the pursuit of certificates versus the achievement of self-directed learning projects [00:36:18] Tips on finding the right type of project to add to your portfolio [00:39:13] For those people a little further along in their career, Kyle shares tips on how to effectively communicate with executives [00:42:16] We talk about our shared love for Bill Murray [00:43:06] How you should respond when you come across job postings that look like they want the skills of an entire team rolled up into one person. [00:46:22] What's the one thing you want people to learn from your story? [00:47:19] The lightning round. Special Guest: Kyle Polich.

Announcing Journal Club I am pleased to announce Data Skeptic is launching a new spin-off show called "Journal Club" with similar themes but a very different format to the Data Skeptic everyone is used to. In Journal Club, we will have a regular panel and occasional guest panelists to discuss interesting news items and one featured journal article every week in a roundtable discussion. Each week, I'll be joined by Lan Guo and George Kemp for a discussion of interesting data science related news articles and a featured journal or pre-print article. We hope that this podcast will give listeners an introduction to the works we cover and how people discuss these works. Our topics will often coincide with the original Data Skeptic podcast's current Interpretability theme, but we have few rules right now or what we pick. We enjoy discussing these items with each other and we hope you will do. In the coming weeks, we will start opening up the guest chair more often to bring new voices to our discussion. After that we'll be looking for ways we can engage with our audience. Keep reading and thanks for listening! Kyle

Welcome to a brand new show from Data Skeptic entitled "Journal Club". Each episode will feature a regular panel and one revolving guest seat. The group will discuss a few topics related to data science and focus on one featured scholarly paper which is discussed in detail. Lan tells the story of a transformer learning to play chess. The experiment was to fine-tune a GPT-2 transformer model using a 2.4M corpus of chess games in standard notation, then to see if it can 'play chess' by generating the next move. This is a thought-provoking way to take advantage of the advances in NLP by 'transforming' a game into the 'language' of written text. This was work done by Shawn Presser. George gives a breakdown of a Kaggle Cheating Scandal where a Grandmaster was caught training on the test set. The story follows Benjamin Minixhofer and his capable detective work to discover an obfuscation that artificially improved the winning team's accuracy. Kyle leads a discussion on the paper Towards A Rigorous Science of Interpretable Machine Learning from Finale Doshi-Velez and Been Kim. The paper is a great survey of the spectrum of interpretability techniques and also contains suggestions for how we describe the "taxonomy" of various methodologies.

We welcome Su Wang back to Data Skeptic to discuss the paper Distributional modeling on a diet: One-shot word learning from text only.

Simon Wardenier introduces you to his top 5 podcasts: Have a listen... 1. Data Skeptic: https://itunes.apple.com/be/podcast/data-skeptic/id890348705?mt=2 2. Marketing School: https://itunes.apple.com/be/podcast/marketing-school-digital-marketing-online-marketing/id1138869817?mt=2 3. The art of paid traffic: https://itunes.apple.com/be/podcast/art-paid-traffic-proven-online-marketing-strategies/id955326572?mt=2 4. Google Partners: https://itunes.apple.com/be/podcast/google-partners/id1206160575?mt=2 5. Tech45: https://itunes.apple.com/be/podcast/tech45/id331894219?mt=2

Lean principles aren’t necessarily new, but someone who has been applying them with great results is Ken Cone. Ken is the CTO and co-owner of Radeus Labs in San Diego, and today he shares with us the 5 S’s of a lean workplace and how his company uses them. On today’s CTO Studio, Ken also tells us where he went to school to hone his tech skills, and where his initial love of technology began. You’ll get to hear all of that and more on this show!  In this episode, you’ll hear: What is peeking up? How do you track a satellite? What is it like to manage hybrid software/hardware teams? How does integrity factor into what they do at Radeus Labs? What is gemba and how does his team use it? And so much more!  To explore how Ken ended up at Radeus Labs and where his love of tech began we go back to his origins. His father was a missionary pastor and they moved to Kodiak Island when Ken was a child. It's an island filled with trees, and bears and deer and other wildlife. Many of the kids on the island played basketball and wrestling, but he was terrible at both so he went hiking and got into computers. His first computer was a Commodore TI994A, which went obsolete shortly after! But it grew his passion for technology. He wanted to design video games so he went to college for computer science engineering at LeTourneau University. At his school they had to complete a senior project for his degree, and he chose to design a single board computer, write the monitor program for it and build it and run it. After school he went to work at Vertex Communications where he wanted to write code. His dream was to design supercomputers that plays video games, and make it accessible for everyone. Although he never got to do that in his day job, he did design an indie game for Xbox with a friend. They called it Andy's Notepad [Saucers], and it had about 300 downloads! Despite having to fulfill his dream outside of his day job, Ken loved and still loves his work. In his 22 years at Vertex, he went from intern to engineer to product manager to operations manager and many titles in between, including director of engineering. During that continuum of roles, Ken also learned about Lean, people management, critical project management so when he was looking for another job his brother-in-law said he'd find him a job in San Diego. That job was at Radeus Labs, and he is currently the co-owner and CTO of the company. In that role for the last few months 25% to 40% of his time over the last few months has been focused on people, from reviews to mentoring to coaching. Of the remaining percentage, he says half of his time is spent on business-related tasks and responsibilities and the other half is technical in nature. As far as the products they create, I was curious to know how to track a satellite. Ken says there are many ways to track a satellite. On the way to this interview he was listening to a podcast, Data Skeptic, and they were talking about a comet filter. One of their competitors at Radeus Labs uses a comet filter to track so he was looking into that as a potential option to improve their customers experience. But in general he says it's actually easy to track a satellite. You can predict where the motion of the moon, the sun, etc. will all be.  They take those parameters and do the math. They know the sun for example was at a certain place at a certain time on a certain date. And because objects in motion tend to stay in motion they can mathematically figure out where the object will be in the future based on its past trajectory. There's much more complexity involved in the algorithms, etc. I was curious how many satellites get destroyed by debris. Ken says the number is significant enough that they have to be aware of it. In fact, this did happen to one of the satellites they were tracking. There was a three month period about a year or two ago they lost four satellites. There are even satellites that have been hit and no one knows what hit them! We also talked about his managing of hybrid software/hardware teams, how data makes it to their DFRs, and his go-to tools for working with his team. He even includes the 5 S’s of Lean: Sort: Physically sort things first Set in place: Put things in place based on how often you use the item Shine: clean it up, make it neat and shiny Standardize: be sure it has been documented and processed so you are doing it the same way every time Sustain: the hardest one to do: the audit to ensure you are doing it the same every single time. Join us to hear how Ken uses each in his workplace and more on today’s episode of CTO Studio.   Episode Resources: Radeus Labs web site Ken Cone on LinkedIn Lean Enterprise Institute web site Managing to Learn, by John Shook Andy's Notepad [Saucers] on YouTube

Kyle Polich is the co-host of the incredibly popular Data Skeptic podcast, which he has been churning out since 2014. He studied computer science and focused on artificial intelligence in grad school. His general interests range from areas like statistics, machine learning, data viz, and optimization to data provenance, data governance, econometrics, and metrology.   The Data Skeptic Podcast features conversations on topics related to data science, statistics, machine learning, and artificial intelligence. The podcast breaks down into two different episode formats. One is a short form podcast where Kyle explains complex data science concepts in a way that non-data scientists can understand. In these episodes he’s joined by his co-host and wife, Linh da Tran. The second format is a long form interview format where Kyle interviews experts in various data science and skepticism related arenas about their work.   In this episode of the Data Journeys Podcast, I pick Kyle’s brain for patterns noticed and lessons learned through interviewing and teaching his way through nearly 400 episodes of the Data Skeptic Podcast. Some of the topics covered include:   How the Data Skeptic podcast became the only podcast to be endorsed by the Pope. Kyle’s approach to teaching complex subject matter for entry level comprehension. What patterns and lessons Kyle has taken from interviewing nearly 400 guests on his show over the last four years. Advice for listeners who are considering starting their own podcasts, colored by lessons Kyle has learned in his tenure. Kyle and I get a little meta in trading lessons, best practices, and common experiences learned from their time hosting podcasts.   Enjoy the show!   Show Notes: https://ajgoldstein.com/podcast/ep20 AJ’s Twitter: https://twitter.com/ajgoldstein393/ Kyle’s LinkedIn: https://www.linkedin.com/in/kyle-polich-5047193

With publications such as "Prior exposure increases perceived accuracy of fake news", "Lazy, not biased: Susceptibility to partisan fake news is better explained by lack of reasoning than by motivated reasoning", and "The science of fake news", Gordon Pennycook is asking and answering analytical questions about the nature of human intuition and fake news. Gordon appeared on Data Skeptic in 2016 to discuss people's ability to recognize pseudo-profound bullshit.  This episode explores his work in fake news.

Medical imaging is a highly effective tool used by clinicians to diagnose a wide array of diseases and injuries. However, it often requires exceptionally trained specialists such as radiologists to interpret accurately. In this episode of Data Skeptic, our host Kyle Polich is joined by Gabriel Maicas, a PhD candidate at the University of Adelaide, to discuss machine learning systems that can be used by radiologists to improve their accuracy and speed of diagnosis.

Data Skeptic is a podcast about machine learning, data science, and how software affects our lives. The first guest on today’s episode is Kyle Polich, the host of Data Skeptic. Kyle is one of the best explainers of machine learning concepts I have met, and for this episode, he presented some material that is perfect The post Machine Learning with Data Skeptic and Second Spectrum at Telesign appeared first on Software Engineering Daily.

Thanks to our sponsor The Great Courses. This week's episode is a short primer on game theory. For tickets to the free Data Skeptic meetup in Chicago on Tuesday, May 15 at the Mendoza College of Business (224 South Michigan Avenue, Suite 350), click here,

In this episode of Data Skeptic, Kyle chats with Jerry Schwarz from the Independent Investigations Group (IIG)'s SF Bay Area chapter about testing claims of the paranormal. The IIG is a volunteer-based organization dedicated to investigating paranormal or extraordinary claim from a scientific viewpoint. The group, headquartered at the Center for Inquiry-Los Angeles in Hollywood, offers a $100,000 prize to anyone who can show, under proper observing conditions, evidence of any paranormal, supernatural, or occult power or event. CHICAGO Tues, May 15, 6pm. Come to our Data Skeptic meetup. CHICAGO Saturday, May 19, 10am. Kyle will be giving a talk at the Chicago AI, Data Science, and Blockchain Conference 2018.

This week on Data Skeptic, we begin with a skit to introduce the topic of this show: The Imitation Game. We open with a scene in the distant future. The year is 2027, and a company called Shamony is announcing their new product, Ada, the most advanced artificial intelligence agent. To prove its superiority, the lead scientist announces that it will use the Turing Test that Alan Turing proposed in 1950. During this we introduce Turing’s “objections” outlined in his famous paper, “Computing Machinery and Intelligence.” Following that, we talk with improv coach Holly Laurent on the art of improvisation and Peter Clark from the Allen Institute for Artificial Intelligence about question and answering algorithms.

Today we are spotlighting Linh Da Tran of Data Skeptic. Data Skeptic covers data science, statistics, machine learning, artificial intelligence, and scientific skepticism. Get your very own WeAreLATech tee at http://wearelatech.com/shop. Connect with us at wearelatech.com/podcast and tweet @WeAreLATech and @EspreeDevora. What is your ask from the community? I'd love for poeple at the top to make a better effort to reach out and help others. https://dataskeptic.com/ https://twitter.com/wearelatech https://twitter.com/espreedevora

Today we get to know Linh Da Tran of Data Skeptic. Data Skeptic covers data science, statistics, machine learning, artificial intelligence, and scientific skepticism. This episode is powered by UpGuard.com, UpGuard's discovery engine brings visibility to complex IT environments, enabling teams to quickly identify risk, confirm compliance and make business safer. Tweet @womenintechshow and @EspreeDevora https://dataskeptic.com/ http://twitter.com/womenintechshow https://twitter.com/espreedevora

Last week on Data Skeptic, we visited the Laboratory of Neuroimaging, or LONI, at USC and learned about their data-driven platform that enables scientists from all over the world to share, transform, store, manage and analyze their data to understand neurological diseases better. We talked about how neuroscientists measure the brain using data from MRI scans, and how that data is processed and analyzed to understand the brain. This week, we'll continue the second half of our two-part episode on LONI.

Last year, Kyle had a chance to visit the Laboratory of Neuroimaging, or LONI, at USC, and learn about how some researchers are using data science to study the function of the brain. We’re going to be covering some of their work in two episodes on Data Skeptic. In this first part of our two-part episode, we'll talk about the data collection and brain imaging and the LONI pipeline. We'll then continue our coverage in the second episode, where we'll talk more about how researchers can gain insights about the human brain and their current challenges. Next week, we’ll also talk more about what all that has to do with data science machine learning and artificial intelligence. Joining us in this week’s episode are members of the LONI lab, which include principal investigators, Dr. Arthur Toga and Dr. Meng Law, and researchers, Farshid Sepherband, PhD and Ryan Cabeen, PhD.

Panel:  Charles Max Wood Guest: Tyler Renelle This week on My Ruby Story, Charles speaks with Tyler Renelle. Tyler is a contractor and developer who has worked in many web technologies like Angular, Rails, React and much more! Tyler is a return guest, previously on Adventure in Angular and JavaScript Jabber talking Ionic and Machine learning. Tyler has recently expanded his work beyond JavaScript and is on the show to talk his interest in AI or Artificial intelligence and Machine Learning. Furthermore, Tyler talks about his early journey as a game developer, web developer, and work with some content management systems, and more recently, his development in various technologies. In particular, we dive pretty deep on: Writing games out of college, studies computer science. Did web development to pay for college working with PHP and ASP Content managements Working with various technologies Working with React, is this it? Problems React has solved with web apps What is the next big innovation? View Creating Podcasts Machine Learning Specialized application of AI NLP Never use his computer science degree as a web developer You don’t study code to be a developer AI and machine learn is based on Computer Science Tensor Flow Data Skeptic - podcast Performance Graphics cards Philosophy of Consciousness The subjective experience Job displacement phenomenon and much, much more! Links:  http://ocdevel.com http://ocdevel.com/podcasts/machine-learning Tensor Flow Data Skeptic - podcast https://devchat.tv/js-jabber/jsj-278-machine-learning-tyler-renelle https://www.linkedin.com/in/lefnire Picks Tyler The Great Courses  Charles CES Email beforehand and setup an appointment VRBO.com Autonomous.ai  

Panel:  Charles Max Wood Guest: Tyler Renelle This week on My Ruby Story, Charles speaks with Tyler Renelle. Tyler is a contractor and developer who has worked in many web technologies like Angular, Rails, React and much more! Tyler is a return guest, previously on Adventure in Angular and JavaScript Jabber talking Ionic and Machine learning. Tyler has recently expanded his work beyond JavaScript and is on the show to talk his interest in AI or Artificial intelligence and Machine Learning. Furthermore, Tyler talks about his early journey as a game developer, web developer, and work with some content management systems, and more recently, his development in various technologies. In particular, we dive pretty deep on: Writing games out of college, studies computer science. Did web development to pay for college working with PHP and ASP Content managements Working with various technologies Working with React, is this it? Problems React has solved with web apps What is the next big innovation? View Creating Podcasts Machine Learning Specialized application of AI NLP Never use his computer science degree as a web developer You don’t study code to be a developer AI and machine learn is based on Computer Science Tensor Flow Data Skeptic - podcast Performance Graphics cards Philosophy of Consciousness The subjective experience Job displacement phenomenon and much, much more! Links:  http://ocdevel.com http://ocdevel.com/podcasts/machine-learning Tensor Flow Data Skeptic - podcast https://devchat.tv/js-jabber/jsj-278-machine-learning-tyler-renelle https://www.linkedin.com/in/lefnire Picks Tyler The Great Courses  Charles CES Email beforehand and setup an appointment VRBO.com Autonomous.ai  

Panel:  Charles Max Wood Guest: Tyler Renelle This week on My Ruby Story, Charles speaks with Tyler Renelle. Tyler is a contractor and developer who has worked in many web technologies like Angular, Rails, React and much more! Tyler is a return guest, previously on Adventure in Angular and JavaScript Jabber talking Ionic and Machine learning. Tyler has recently expanded his work beyond JavaScript and is on the show to talk his interest in AI or Artificial intelligence and Machine Learning. Furthermore, Tyler talks about his early journey as a game developer, web developer, and work with some content management systems, and more recently, his development in various technologies. In particular, we dive pretty deep on: Writing games out of college, studies computer science. Did web development to pay for college working with PHP and ASP Content managements Working with various technologies Working with React, is this it? Problems React has solved with web apps What is the next big innovation? View Creating Podcasts Machine Learning Specialized application of AI NLP Never use his computer science degree as a web developer You don’t study code to be a developer AI and machine learn is based on Computer Science Tensor Flow Data Skeptic - podcast Performance Graphics cards Philosophy of Consciousness The subjective experience Job displacement phenomenon and much, much more! Links:  http://ocdevel.com http://ocdevel.com/podcasts/machine-learning Tensor Flow Data Skeptic - podcast https://devchat.tv/js-jabber/jsj-278-machine-learning-tyler-renelle https://www.linkedin.com/in/lefnire Picks Tyler The Great Courses  Charles CES Email beforehand and setup an appointment VRBO.com Autonomous.ai  

This episode kicks off the next theme on Data Skeptic: artificial intelligence.  Kyle discusses what's to come for the show in 2018, why this topic is relevant, and how we intend to cover it.

Panel:  Charles Max Wood Guest: Tyler Renelle This week on My JavaScript Story, Charles speaks with Tyler Renelle. Tyler is a contractor and developer who has worked in many web technologies like Angular, Rails, React and much more! Tyler is a return guest, previously on Adventure in Angular and JavaScript Jabber talking Ionic and Machine learning. Tyler has recently expanded his work beyond JavaScript and is on the show to talk his interest in AI or Artificial intelligence and Machine Learning. Furthermore, Tyler talks about his early journey as a game developer, web developer, and work with some content management systems, and more recently, his development in various technologies. In particular, we dive pretty deep on: Writing games out of college Studies computer science in college Did web development to pay for college working with PHP and ASP Content management Working with various technologies Working with React, is this it? Problems React has solved with web apps What is the next big innovation? View Creating Podcasts Machine Learning Specialized application of AI NLP Never use his computer science degree as a web developer You don’t study code to be a developer AI and machine learn is based on Computer Science Tensor Flow Data Skeptic - podcast Performance Graphics cards Philosophy of Consciousness The subjective experience Job displacement phenomenon and much, much more! Links:  http://ocdevel.com http://ocdevel.com/podcasts/machine-learning Tensor Flow Data Skeptic - podcast https://devchat.tv/js-jabber/jsj-278-machine-learning-tyler-renelle https://www.linkedin.com/in/lefnire Picks Tyler The Great Courses  Charles CES Email beforehand and set up an appointment VRBO.com Autonomous.ai  

Panel:  Charles Max Wood Guest: Tyler Renelle This week on My JavaScript Story, Charles speaks with Tyler Renelle. Tyler is a contractor and developer who has worked in many web technologies like Angular, Rails, React and much more! Tyler is a return guest, previously on Adventure in Angular and JavaScript Jabber talking Ionic and Machine learning. Tyler has recently expanded his work beyond JavaScript and is on the show to talk his interest in AI or Artificial intelligence and Machine Learning. Furthermore, Tyler talks about his early journey as a game developer, web developer, and work with some content management systems, and more recently, his development in various technologies. In particular, we dive pretty deep on: Writing games out of college Studies computer science in college Did web development to pay for college working with PHP and ASP Content management Working with various technologies Working with React, is this it? Problems React has solved with web apps What is the next big innovation? View Creating Podcasts Machine Learning Specialized application of AI NLP Never use his computer science degree as a web developer You don’t study code to be a developer AI and machine learn is based on Computer Science Tensor Flow Data Skeptic - podcast Performance Graphics cards Philosophy of Consciousness The subjective experience Job displacement phenomenon and much, much more! Links:  http://ocdevel.com http://ocdevel.com/podcasts/machine-learning Tensor Flow Data Skeptic - podcast https://devchat.tv/js-jabber/jsj-278-machine-learning-tyler-renelle https://www.linkedin.com/in/lefnire Picks Tyler The Great Courses  Charles CES Email beforehand and set up an appointment VRBO.com Autonomous.ai  

Panel:  Charles Max Wood Guest: Tyler Renelle This week on My JavaScript Story, Charles speaks with Tyler Renelle. Tyler is a contractor and developer who has worked in many web technologies like Angular, Rails, React and much more! Tyler is a return guest, previously on Adventure in Angular and JavaScript Jabber talking Ionic and Machine learning. Tyler has recently expanded his work beyond JavaScript and is on the show to talk his interest in AI or Artificial intelligence and Machine Learning. Furthermore, Tyler talks about his early journey as a game developer, web developer, and work with some content management systems, and more recently, his development in various technologies. In particular, we dive pretty deep on: Writing games out of college Studies computer science in college Did web development to pay for college working with PHP and ASP Content management Working with various technologies Working with React, is this it? Problems React has solved with web apps What is the next big innovation? View Creating Podcasts Machine Learning Specialized application of AI NLP Never use his computer science degree as a web developer You don’t study code to be a developer AI and machine learn is based on Computer Science Tensor Flow Data Skeptic - podcast Performance Graphics cards Philosophy of Consciousness The subjective experience Job displacement phenomenon and much, much more! Links:  http://ocdevel.com http://ocdevel.com/podcasts/machine-learning Tensor Flow Data Skeptic - podcast https://devchat.tv/js-jabber/jsj-278-machine-learning-tyler-renelle https://www.linkedin.com/in/lefnire Picks Tyler The Great Courses  Charles CES Email beforehand and set up an appointment VRBO.com Autonomous.ai  

Dharma Shukla is a distinguished Engineer at Microsoft. He is the General Manager of Azure Cosmos DB. He is the founder of Azure Cosmos DB, which was launched officially in May 2017. It is Microsoft’s globally-distributed, multi-model database service for managing data at planet-scale". One interesting cool fact about him that he has more than 60 patents in technology industry and he is a long distance runner. Interviewer: Rajib Bahar & Shabnam Khan Agenda: SB - Why the name Cosmos? How did Cosmos DB started at Microsoft? Or Why did you decide to build Cosmos DB? We heard that it is used extensively within Microsoft, is it true? RB - What is the programming language in which Cosmos DB is written? SB - What makes Cosmos DB special? Can you give us more insights into its capabilities? (resume) RB - When we heard your podcast episode in Data Skeptic, there was a mention of "Auto Index". You explained it quite well at high level and how it gives freedom to developer from worries related to indexing as their application scale up. Our follow up question to that is how does this Auto-indexing work internally? Does Cosmos keep track of most used data internally in some kind of table/tree structure to determine this? Is this based on an existing algorithm in Computer Science realm or something propriety? SB - Can you tell us more about the new capabilities and features your team is working on? RB - We see that Cosmos DB keeps shipping new features every few weeks. Can you tell us how do you roll out new features? SB - How do we connect with you in Twitter or other professional network or blogs? Music: www.freesfx.co.uk

Over the past several years, we have seen many success stories in machine learning brought about by deep learning techniques. While the practical success of deep learning has been phenomenal, the formal guarantees have been lacking. Our current theoretical understanding of the many techniques that are central to the current ongoing big-data revolution is far from being sufficient for rigorous analysis, at best. In this episode of Data Skeptic, our host Kyle Polich welcomes guest John Wilmes, a mathematics post-doctoral researcher at Georgia Tech, to discuss the efficiency of neural network learning through complexity theory.

Tweet this Episode Tyler Renelle is a contractor and developer who has worked in various web technologies like Node, Angular, Rails, and much more. He's also build machine learning backends in Python (Flask), Tensorflow, and Neural Networks. The JavaScript Jabber panel dives into Machine Learning with Tyler Renelle. Specifically, they go into what is emerging in machine learning and artificial intelligence and what that means for programmers and programming jobs. This episode dives into: Whether machine learning will replace programming jobs Economic automation Which platforms and languages to use to get into machine learning and much, much more... Links: Raspberry Pi Arduino Hacker News Neural Networks (wikipedia) Deep Mind Shallow Algorithms Genetic Algorithms Crisper gene editing Wix thegrid.io Codeschool Codecademy Tensorflow Keras Machine Learning Guide Andrew Ng Coursera Course Python R Java Torch PyTorch Caffe Scikit learn Tensorfire DeepLearn.js The Singularity is Near by Ray Kurzweil Tensorforce Super Intelligence by Nick Bostrom Picks: Aimee Include media Nodevember Phone cases AJ Data Skeptic Ready Player One Joe Everybody Lies Tyler Ex Machina Philosophy of Mind: Brains, Consciousness, and Thinking Machines

Tweet this Episode Tyler Renelle is a contractor and developer who has worked in various web technologies like Node, Angular, Rails, and much more. He's also build machine learning backends in Python (Flask), Tensorflow, and Neural Networks. The JavaScript Jabber panel dives into Machine Learning with Tyler Renelle. Specifically, they go into what is emerging in machine learning and artificial intelligence and what that means for programmers and programming jobs. This episode dives into: Whether machine learning will replace programming jobs Economic automation Which platforms and languages to use to get into machine learning and much, much more... Links: Raspberry Pi Arduino Hacker News Neural Networks (wikipedia) Deep Mind Shallow Algorithms Genetic Algorithms Crisper gene editing Wix thegrid.io Codeschool Codecademy Tensorflow Keras Machine Learning Guide Andrew Ng Coursera Course Python R Java Torch PyTorch Caffe Scikit learn Tensorfire DeepLearn.js The Singularity is Near by Ray Kurzweil Tensorforce Super Intelligence by Nick Bostrom Picks: Aimee Include media Nodevember Phone cases AJ Data Skeptic Ready Player One Joe Everybody Lies Tyler Ex Machina Philosophy of Mind: Brains, Consciousness, and Thinking Machines

Tweet this Episode Tyler Renelle is a contractor and developer who has worked in various web technologies like Node, Angular, Rails, and much more. He's also build machine learning backends in Python (Flask), Tensorflow, and Neural Networks. The JavaScript Jabber panel dives into Machine Learning with Tyler Renelle. Specifically, they go into what is emerging in machine learning and artificial intelligence and what that means for programmers and programming jobs. This episode dives into: Whether machine learning will replace programming jobs Economic automation Which platforms and languages to use to get into machine learning and much, much more... Links: Raspberry Pi Arduino Hacker News Neural Networks (wikipedia) Deep Mind Shallow Algorithms Genetic Algorithms Crisper gene editing Wix thegrid.io Codeschool Codecademy Tensorflow Keras Machine Learning Guide Andrew Ng Coursera Course Python R Java Torch PyTorch Caffe Scikit learn Tensorfire DeepLearn.js The Singularity is Near by Ray Kurzweil Tensorforce Super Intelligence by Nick Bostrom Picks: Aimee Include media Nodevember Phone cases AJ Data Skeptic Ready Player One Joe Everybody Lies Tyler Ex Machina Philosophy of Mind: Brains, Consciousness, and Thinking Machines

AiA 149: Angular, Web Bluetooth, and IoT with Uri Shaked In this episode, Shai Reznik, Ward Bell, Lukas Ruebbelke, and Charles Max Wood talk to Uri Shaked about using Angular with Web Bluetooth and IoT. [00:02:27] – Introduction to Uri Shaked Uri is an Angular GDE from Israel. His Angular Story episode is here. [00:03:21] – Introduction to Hardware with Angular Angular allows you to build web applications that scale quickly. For hardware devices, you need some kind of interface. Instead of a button, you have a mobile app or web application. This is one place where Angular comes into play. Building control panels, etc. You can do this with pure JavaScript or native mobile apps as well. [00:05:20] – Does it run on the IoT device? or on the web? It can do both. You can run Angular on a webserver on a Raspberry Pi or you can use Web Bluetooth to connect to the IoT device. [00:06:45] – What are the advantages of using web technologies? There's no hardware setup. And using Angular Material or Ionic, the UI looks right without spending a ton of time. RxJS allows you to gather sensor data from accelerometers, heart rate monitors, etc. connected via bluetooth. [00:09:20] – The physical web An IoT device that broadcasts its own URL. You can then interface with the device simply by scanning for and browsing to the device. One example is walking into a room, scanning, and then controlling the lights without installing an app. [00:10:34] – Security Security is optional on Bluetooth Low Energy. Bluetooth devices used to pair using pin codes and they got set to 0000 or 1234 by default. So now BLE devices don't require it. Some devices add security on top of bluetooth or use the pairing mechanism. Security is an ongoing concern with IoT in general. The devices that Uri has played with don't implement security. Uri actually had an audience member hack into the smart bulb he was using during a demo. [00:15:08] – How do you manage your connection to the device through Angular? Uri uses async/await to manage the promises based functions that allow you to connect to the device. He wraps all of this in a service. The bluetooth terminology used for the functions that manage the device are also called services. Don't get them confused. [00:16:48] – What's the most useful thing you can do with this? Connecting to an EEG headset that measures brainwaves. Uri wants to allow headset owners to perform EEG experiments in the browser. Otherwise, they have to set up a bluetooth dongle and install python and some libraries to make it work. He'd like to make it simple enough to browse to a webpage and click "Connect." He'd like to show the user pictures and then guess which one you're looking at. [00:19:58] – What is the most useless thing you've build with this? Uri 3D-printed a robot and installed an accelerometer into it and connected it to a WebGL based system to show the orientation of the robot. [00:22:32] – How do you get started? You need a browser and a bluetooth device. A smart lightbulb or a robot. You can use your smartphone to simulate a bluetooth device. Uri wrote an Android app that simulates a smart light bulb. Then you can connect the app to your computer's browser and control the smart bulb app from your computer. [00:25:00] – Ward has a proposal for Uri Connect lights in your t-shirt to an arduino device and control it from your phone.  Web Bluetooth is much simpler than native APIs for Android or iOS. [00:29:45] – Commercial applications Physical web applications and connecting to remote tools and sensors. Smart counters for your electric meter. Jen Looper's blog post on web bluetooth and beacons. The Louvre uses beacons. [00:33:00] – The physical web Uri ran a beacon that broadcast his personal site. He took his trash out and one of his neighbors kept getting a notification about his website on his phone. Picks Lukas Ruebbelke Antifragile Chef's Table on Netflix Shai Reznik 59 Seconds Volunteering - Ari Lerner teaching prisoners to code Ward Bell The "other" Uri Shaked Smart Coffee Machine YouTube video on telling if someone is lying Uri Shaked Ward's yet-to-be-made shirt AngularUP Conference WebAssembly Charles Max Wood Data Skeptic podcast Links @urishaked urish.org

AiA 149: Angular, Web Bluetooth, and IoT with Uri Shaked In this episode, Shai Reznik, Ward Bell, Lukas Ruebbelke, and Charles Max Wood talk to Uri Shaked about using Angular with Web Bluetooth and IoT. [00:02:27] – Introduction to Uri Shaked Uri is an Angular GDE from Israel. His Angular Story episode is here. [00:03:21] – Introduction to Hardware with Angular Angular allows you to build web applications that scale quickly. For hardware devices, you need some kind of interface. Instead of a button, you have a mobile app or web application. This is one place where Angular comes into play. Building control panels, etc. You can do this with pure JavaScript or native mobile apps as well. [00:05:20] – Does it run on the IoT device? or on the web? It can do both. You can run Angular on a webserver on a Raspberry Pi or you can use Web Bluetooth to connect to the IoT device. [00:06:45] – What are the advantages of using web technologies? There's no hardware setup. And using Angular Material or Ionic, the UI looks right without spending a ton of time. RxJS allows you to gather sensor data from accelerometers, heart rate monitors, etc. connected via bluetooth. [00:09:20] – The physical web An IoT device that broadcasts its own URL. You can then interface with the device simply by scanning for and browsing to the device. One example is walking into a room, scanning, and then controlling the lights without installing an app. [00:10:34] – Security Security is optional on Bluetooth Low Energy. Bluetooth devices used to pair using pin codes and they got set to 0000 or 1234 by default. So now BLE devices don't require it. Some devices add security on top of bluetooth or use the pairing mechanism. Security is an ongoing concern with IoT in general. The devices that Uri has played with don't implement security. Uri actually had an audience member hack into the smart bulb he was using during a demo. [00:15:08] – How do you manage your connection to the device through Angular? Uri uses async/await to manage the promises based functions that allow you to connect to the device. He wraps all of this in a service. The bluetooth terminology used for the functions that manage the device are also called services. Don't get them confused. [00:16:48] – What's the most useful thing you can do with this? Connecting to an EEG headset that measures brainwaves. Uri wants to allow headset owners to perform EEG experiments in the browser. Otherwise, they have to set up a bluetooth dongle and install python and some libraries to make it work. He'd like to make it simple enough to browse to a webpage and click "Connect." He'd like to show the user pictures and then guess which one you're looking at. [00:19:58] – What is the most useless thing you've build with this? Uri 3D-printed a robot and installed an accelerometer into it and connected it to a WebGL based system to show the orientation of the robot. [00:22:32] – How do you get started? You need a browser and a bluetooth device. A smart lightbulb or a robot. You can use your smartphone to simulate a bluetooth device. Uri wrote an Android app that simulates a smart light bulb. Then you can connect the app to your computer's browser and control the smart bulb app from your computer. [00:25:00] – Ward has a proposal for Uri Connect lights in your t-shirt to an arduino device and control it from your phone.  Web Bluetooth is much simpler than native APIs for Android or iOS. [00:29:45] – Commercial applications Physical web applications and connecting to remote tools and sensors. Smart counters for your electric meter. Jen Looper's blog post on web bluetooth and beacons. The Louvre uses beacons. [00:33:00] – The physical web Uri ran a beacon that broadcast his personal site. He took his trash out and one of his neighbors kept getting a notification about his website on his phone. Picks Lukas Ruebbelke Antifragile Chef's Table on Netflix Shai Reznik 59 Seconds Volunteering - Ari Lerner teaching prisoners to code Ward Bell The "other" Uri Shaked Smart Coffee Machine YouTube video on telling if someone is lying Uri Shaked Ward's yet-to-be-made shirt AngularUP Conference WebAssembly Charles Max Wood Data Skeptic podcast Links @urishaked urish.org

AiA 149: Angular, Web Bluetooth, and IoT with Uri Shaked In this episode, Shai Reznik, Ward Bell, Lukas Ruebbelke, and Charles Max Wood talk to Uri Shaked about using Angular with Web Bluetooth and IoT. [00:02:27] – Introduction to Uri Shaked Uri is an Angular GDE from Israel. His Angular Story episode is here. [00:03:21] – Introduction to Hardware with Angular Angular allows you to build web applications that scale quickly. For hardware devices, you need some kind of interface. Instead of a button, you have a mobile app or web application. This is one place where Angular comes into play. Building control panels, etc. You can do this with pure JavaScript or native mobile apps as well. [00:05:20] – Does it run on the IoT device? or on the web? It can do both. You can run Angular on a webserver on a Raspberry Pi or you can use Web Bluetooth to connect to the IoT device. [00:06:45] – What are the advantages of using web technologies? There's no hardware setup. And using Angular Material or Ionic, the UI looks right without spending a ton of time. RxJS allows you to gather sensor data from accelerometers, heart rate monitors, etc. connected via bluetooth. [00:09:20] – The physical web An IoT device that broadcasts its own URL. You can then interface with the device simply by scanning for and browsing to the device. One example is walking into a room, scanning, and then controlling the lights without installing an app. [00:10:34] – Security Security is optional on Bluetooth Low Energy. Bluetooth devices used to pair using pin codes and they got set to 0000 or 1234 by default. So now BLE devices don't require it. Some devices add security on top of bluetooth or use the pairing mechanism. Security is an ongoing concern with IoT in general. The devices that Uri has played with don't implement security. Uri actually had an audience member hack into the smart bulb he was using during a demo. [00:15:08] – How do you manage your connection to the device through Angular? Uri uses async/await to manage the promises based functions that allow you to connect to the device. He wraps all of this in a service. The bluetooth terminology used for the functions that manage the device are also called services. Don't get them confused. [00:16:48] – What's the most useful thing you can do with this? Connecting to an EEG headset that measures brainwaves. Uri wants to allow headset owners to perform EEG experiments in the browser. Otherwise, they have to set up a bluetooth dongle and install python and some libraries to make it work. He'd like to make it simple enough to browse to a webpage and click "Connect." He'd like to show the user pictures and then guess which one you're looking at. [00:19:58] – What is the most useless thing you've build with this? Uri 3D-printed a robot and installed an accelerometer into it and connected it to a WebGL based system to show the orientation of the robot. [00:22:32] – How do you get started? You need a browser and a bluetooth device. A smart lightbulb or a robot. You can use your smartphone to simulate a bluetooth device. Uri wrote an Android app that simulates a smart light bulb. Then you can connect the app to your computer's browser and control the smart bulb app from your computer. [00:25:00] – Ward has a proposal for Uri Connect lights in your t-shirt to an arduino device and control it from your phone.  Web Bluetooth is much simpler than native APIs for Android or iOS. [00:29:45] – Commercial applications Physical web applications and connecting to remote tools and sensors. Smart counters for your electric meter. Jen Looper's blog post on web bluetooth and beacons. The Louvre uses beacons. [00:33:00] – The physical web Uri ran a beacon that broadcast his personal site. He took his trash out and one of his neighbors kept getting a notification about his website on his phone. Picks Lukas Ruebbelke Antifragile Chef's Table on Netflix Shai Reznik 59 Seconds Volunteering - Ari Lerner teaching prisoners to code Ward Bell The "other" Uri Shaked Smart Coffee Machine YouTube video on telling if someone is lying Uri Shaked Ward's yet-to-be-made shirt AngularUP Conference WebAssembly Charles Max Wood Data Skeptic podcast Links @urishaked urish.org

Engineers have plenty to be skeptical about. We look to data sets to give us something resembling objective truth. Some areas of research have so many variables that it is hard to isolate facts. Kyle Polich hosts the popular data science show Data Skeptic, where he examines problems and solutions around data, and he is The post Skepticism Roundtable with Ammon Bartram and Kyle Polich appeared first on Software Engineering Daily.

This episode is from the Data Skeptic archives. I spoke to Ang Nuygen back in 2015 about his paper "Deep Neural Networks are Easily Fooled". This is another great example of Adversarial Learning so we wanted to re-release this episode for anyone that missed it or wants a refresher.

Featured recently on Data Skeptic, this is the full interview with Jill Darling

So what's the deal with the bonus feed? How does it relate to the main Data Skeptic podcast? Answers within!

No reliable, complete database cataloging home sales data at a transaction level is available for the average person to access. To a data scientist interesting in studying this data, our hands are complete tied. Opportunities like testing sociological theories, exploring economic impacts, study market forces, or simply research the value of an investment when buying a home are all blocked by the lack of easy access to this dataset. OpenHouse seeks to correct that by centralizing and standardizing all publicly available home sales transactional data. In this episode, we discuss the achievements of OpenHouse to date, and what plans exist for the future. Check out the OpenHouse gallery. I also encourage everyone to check out the project Zareen mentioned which was her Harry Potter word2vec webapp and Joy's project doing data visualization on Jawbone data. Guests Thanks again to @iamzareenf, @blueplastic, and @joytafty for coming on the show. Thanks to the numerous other volunteers who have helped with the project as well! Announcements and details If you're interested in getting involved in OpenHouse, check out the OpenHouse contributor's quickstart page. Kyle is giving a machine learning talk in Los Angeles on May 25th, 2017 at Zehr. Sponsor Thanks to our sponsor for this episode Periscope Data. The blog post demoing their maps option is on our blog titled Periscope Data Maps. To start a free trial of their dashboarding too, visit http://periscopedata.com/skeptics Kyle recently did a youtube video exploring the Data Skeptic podcast download numbers using Periscope Data. Check it out at https://youtu.be/aglpJrMp0M4. Supplemental music is Lee Rosevere's Let's Start at the Beginning.  

  In this week's episode of Data Skeptic, host Kyle Polich talks with guest Maura Church, Patreon's data science manager. Patreon is a fast-growing crowdfunding platform that allows artists and creators of all kinds build their own subscription content service. The platform allows fans to become patrons of their favorite artists- an idea similar the Renaissance times, when musicians would rely on benefactors to become their patrons so they could make more art. At Patreon, Maura's data science team strives to provide creators with insight, information, and tools, so that creators can focus on what they do best-- making art. On the show, Maura talks about some of her projects with the data science team at Patreon. Among the several topics discussed during the episode include: optical music recognition (OMR) to translate musical scores to electronic format, network analysis to understand the connection between creators and patrons, growth forecasting and modeling in a new market, and churn modeling to determine predictors of long time support. A more detailed explanation of Patreon's A/B testing framework can be found here Other useful links to topics mentioned during the show: OMR research Patreon blog Patreon HQ blog Amanda Palmer Fran Meneses

In this Data Skeptic episode, Kyle is joined by guest Ruggiero Cavallo to discuss his latest efforts to mitigate the problems presented in this new world of online advertising. Working with his collaborators, Ruggiero reconsiders the search ad allocation and pricing problems from the ground up and redesigns a search ad selling system. He discusses a mechanism that optimizes an entire page of ads globally based on efficiency-maximizing search allocation and a novel technical approach to computing prices.

Today on Data Skeptic, Lachlan Gunn joins us to discuss his recent paper Too Good to be True. This paper highlights a somewhat paradoxical / counterintuitive fact about how unanimity is unexpected in cases where perfect measurements cannot be taken. With large enough data, some amount of error is expected. The "Too Good to be True" paper highlights three interesting examples which we discuss in the podcast. You can also watch a lecture from Lachlan on this topic via youtube here.

This episode is a discussion of multiple regression: the use of observations that are a vector of values to predict a response variable. For this episode, we consider how features of a home such as the number of bedrooms, number of bathrooms, and square footage can predict the sale price. Unlike a typical episode of Data Skeptic, these show notes are not just supporting material, but are actually featured in the episode. The site Redfin gratiously allows users to download a CSV of results they are viewing. Unfortunately, they limit this extract to 500 listings, but you can still use it to try the same approach on your own using the download link shown in the figure below.

A recent paper in the journal of Judgment and Decision Making titled On the reception and detection of pseudo-profound bullshit explores empirical questions around a reader's ability to detect statements which may sound profound but are actually a collection of buzzwords that fail to contain adequate meaning or truth. These statements are definitively different from lies and nonesense, as we discuss in the episode. This paper proposes the Bullshit Receptivity scale (BSR) and empirically demonstrates that it correlates with existing metrics like the Cognitive Reflection Test, building confidence that this can be a useful, repeatable, empirical measure of a person's ability to detect pseudo-profound statements as being different from genuinely profound statements. Additionally, the correlative results provide some insight into possible root causes for why individuals might find great profundity in these statements based on other beliefs or cognitive measures. The paper's lead author Gordon Pennycook joins me to discuss this study's results. If you'd like some examples of pseudo-profound bullshit, you can randomly generate some based on Deepak Chopra's twitter feed. To read other work from Gordon, check out his Google Scholar page and find him on twitter via @GordonPennycook. And just for fun, if you think you've dreamed up a Data Skeptic related pseudo-profound bullshit statement, tweet it with hashtag #pseudoprofound. If I see an especially clever or humorous one, I might want to send you a free Data Skeptic sticker.  

This episode is a discussion of data visualization and a proposed New Year's resolution for Data Skeptic listeners. Let's kill the word cloud.

Today's episode is a reading of Isaac Asimov's The Machine that Won the War. I can't think of a story that's more appropriate for Data Skeptic.

Today's guest is Cameron Davidson-Pilon. Cameron has a masters degree in quantitative finance from the University of Waterloo. Think of it as statistics on stock markets. For the last two years he's been the team lead of data science at Shopify. He's the founder of dataoragami.net which produces screencasts teaching methods and techniques of applied data science. He's also the author of the just released in print book Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference, which you can also get in a digital form. This episode focuses on the topic of Bayesian A/B Testing which spans just one chapter of the book. Related to today's discussion is the Data Origami post The class imbalance problem in A/B testing. Lastly, Data Skeptic will be giving away a copy of the print version of the book to one lucky listener who has a US based delivery address. To participate, you'll need to write a review of any site, book, course, or podcast of your choice on datasciguide.com. After it goes live, tweet a link to it with the hashtag #WinDSBook to be given an entry in the contest. This contest will end November 20th, 2015, at which time I'll draw a single randomized winner and contact them for delivery details via direct message on Twitter.

How do people think rationally about small probability events? What is the optimal statistical process by which one can update their beliefs in light of new evidence? This episode of Data Skeptic explores questions like this as Kyle consults a cast of previous guests and experts to try and answer the question "What is the probability, however small, that Bigfoot is real?"

Kyle Polich of the Data Skeptic Podcast comes on to talk about The Bible Code.