Podcast appearances and mentions of tyler renelle

Heard a lot about AI and Machine Learning but don't understand it?  This month's episode is for you: we're introducing machine learning in the simplest way possible, as if we were chatting with a five-year-old!   Special guest Tyler Renelle, host of Dept's Machine Learning Guide podcast, sits down with with Dept Engineer and Resident Five Year Old, Matt Merrill to teach him about the history, background and technical landscape of machine learning. Just enough to get anyone, even an actual five-year-old, started!

Ahmad Mustafa Anis joins the adventure to discuss how he deploys his Machine Learning models using FastAPI. FastAPI is a system for connecting and running Python programs. If your model is built in Python, you can use FastAPI to deploy to Heroku or similar services. Panel Ben WilsonCharles Max WoodFrancois Bertrand Guest Ahmad Mustafa Anis Sponsors Dev Influencers AcceleratorLevel Up | Devchat.tv Links How to deploy Machine Learning/Deep Learning models to the webMachine Learning Guide PodcastAhmad Anis, Author at cnvrgAhmad Anis - KDnuggetsLinkedIn: Ahmad AnisGitHub: Ahmad Mustafa Anis ( ahmadmustafaanis ) Twitter: Ahmad Mustafa Anis ( @AhmadMustafaAn1 ) Picks Ahmad- Deep Learning for Coders with Fastai and PyTorchBen- Arcadia: A NovelCharles- JSJ 278 Machine Learning with Tyler RenelleCharles- X: Multiply Your God-Given Potential Charles- The Art of Impossible: A Peak Performance Primer Charles- Lost Ruins of ArnakCharles- Steampunk Rally Charles- Gods Love Dinosaurs Francois- Will and Vision: How Latecomers Grow to Dominate Markets Contact Ben: DatabricksGitHub | BenWilson2/ML-EngineeringGitHub | databrickslabs/automl-toolkitLinkedIn: Benjamin Wilson Contact Charles: Devchat.tvDevChat.tv | FacebookTwitter: DevChat.tv ( @devchattv ) Contact Francois: Francois BertrandGitHub | fbdesignpro/sweetviz Special Guest: Ahmad Mustafa Anis.

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  

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  

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

Tyler Renelle is the creator and co-founder of Habitica, an app that turns your everyday tasks and habits into a video gameWe talk about the road from an idea to the successful Kickstarter of HabiticaHabitica is very complex, but uses strategies form games to ease users into creating new habitsMany people claimed to hold the secret to effective habit-forming, but Habitica sampled from many different games to create something that fits a variety of peopleTyler turns a bad World of Warcraft habit into the catalyst for self-improvementGoogle Deepmind and the curious way that games play a role in human progressLinks HabiticaGoogle DeepMindHow games spurred the invention of probability theory  +++++++ Share this Episode: 1-click Twitter share 1-click Facebook share 1-click Google + share Link to this episode +++++++ About +7 Intelligence +7 Intelligence is the podcast about how games impact people. Each episode explores a different perspective on how games profoundly influence the real world. Interviews with game designers, psychologists, professionals, and everyday players discuss the unique way that games influence their life and work. +++++++ Listen to the show: Apple Podcasts | Android | Spotify | Stitcher | Google Play | Radiopublic RSS feed Find the show online: +7 Intelligence Website On Twitter: @7_Intelligence On Facebook: @plus7intelligence +7 Intelligence is a member of the Podglomerate ... Learn more about your ad choices. Visit megaphone.fm/adchoices

RR 319 Machine Learning with Tyler Renelle This episode of the Ruby Rogues Panel features panelists Charles Max Wood and Dave Kimura. Tyler Renelle, who stops by to talk about machine learning, joins them as a guest. Tyler is the first guest to talk on Adventures in Angular, JavaScript Jabber, and Ruby Rogues. Tune in to find out more about Tyler and machine learning! What is machine learning? Machine learning is a different concept than programmers are used to. There are three phases in computing technology. First phase – building computers in the first place but it was hard coded onto the physical computing machinery Second phase – programmable computers. Where you can reprogram your computer to do anything. This is the phase where programmers fall. Third phase – machine learning falls under this phase. Machine learning is where the computer programs itself to do something. You give the computer a measurement of how it’s doing based on data and it trains itself and learns how to do the task. It is beginning to get a lot of press and become more popular. This is because it is becoming a lot more capable by way of deep learning. AI – Artificial Intelligence Machine learning is a sub field of artificial intelligence. AI is an overarching field of the computer simulating intelligence. Machine learning has become less and less a sub field over time and more a majority of AI. Now we can apply machine learning to vision, speech processing, planning, knowledge representation. This is fast taking over AI. People are beginning to consider the terms artificial intelligence and machine learning synonymous. Self-driving cars are a type of artificial intelligence. The connection between machine learning and self-driving cars is abstract. A fundamental thing in self-driving cars is machine learning. You program the car as to how to fix its mistakes. Another example is facial recognition. The program starts learning about a person’s face over time so it can make an educated guess as to if the person is who they say they are. Once statistics are added then your face can be off by a hair or a hat. Small variations won’t throw it off. How do we start solving the problems we want to be solved? Machine learning has been applied since the 1950s to a broad spectrum of problems. Have to have a little bit of domain knowledge and do some research. Machine Learning Vs Programming Machine learning is any sort of fuzzy programming situation. Programming is when you do things specifically or statically. Why should you care to do machine learning? People should care because this is the next wave of computing. There is a theory that this will displace jobs. Self-driving cars will displace truck drivers, Uber drivers, and taxis. There are things like logo generators already. Machines are generating music, poetry, and website designs. We shouldn’t be afraid that we should keep an eye towards it. If a robot or computer program or AI were able to write its own code, at what point would it be able to overwrite or basically nullify the three laws of robotics? Nick Bostrom wrote the book Superintelligence, which had many big names in technology talking about the dangers of AI. Artificial intelligence has been talked about widely because of the possibility of evil killer robots in the Sci-Fi community. There are people who hold very potential concerns, such as job automation. Consciousness is a huge topic of debate right now on this topic. Is it an emergent property of the human brain? Is what we have with deep learning enough of a representation to achieve consciousness? It is suggested that AI may or may not achieve consciousness. The question is if it is able to achieve consciousness - will we be able to tell there isn’t a person there? If people want to dive into this where do they go? Machine Learning Guide Podcast: http://ocdevel.com/podcasts/machine-learning The Master Algorithm. https://www.amazon.com/Master-Algorithm-Ultimate-Learning-Machine/dp/0465065708 Andrew Ng course: coursera.org/machine/learning Machine Learning Language The main language used for machine learning is Python. This is not because of the language itself, but because of the tools built on top of it. The main framework is TensorFlow. Python in TensorFlow drops to C and executes code on the GPU for performing matrix algebra, which is essential for deep learning. You can always use C, C++, Java, and R. Data scientists mostly use R, while researchers use C and C++ so they can custom code their matrix algebra themselves. Picks Dave: 20-gallon Husky oil free air compressor: http://www.homedepot.com/p/Husky-20-Gal-Vertical-Oil-Free-Electric-Air-Compressor-0332013/207040335 Charles: Twitter T gem: https://rubygems.org/gems/t/versions/2.10.0> Ruby Dev Summit: www.rubydevsummit.com Rake: https://www.sitepoint.com/rake-automate-things/ Tyler: Machine Learning Guide Podcast: http://ocdevel.com/podcasts/machine-learning Philosophy of Mind: Brains, Consciousness, and Thinking Machines (The Great Courses): https://www.amazon.com/Great-Courses-Philosophy-Mind/dp/1598034243

RR 319 Machine Learning with Tyler Renelle This episode of the Ruby Rogues Panel features panelists Charles Max Wood and Dave Kimura. Tyler Renelle, who stops by to talk about machine learning, joins them as a guest. Tyler is the first guest to talk on Adventures in Angular, JavaScript Jabber, and Ruby Rogues. Tune in to find out more about Tyler and machine learning! What is machine learning? Machine learning is a different concept than programmers are used to. There are three phases in computing technology. First phase – building computers in the first place but it was hard coded onto the physical computing machinery Second phase – programmable computers. Where you can reprogram your computer to do anything. This is the phase where programmers fall. Third phase – machine learning falls under this phase. Machine learning is where the computer programs itself to do something. You give the computer a measurement of how it’s doing based on data and it trains itself and learns how to do the task. It is beginning to get a lot of press and become more popular. This is because it is becoming a lot more capable by way of deep learning. AI – Artificial Intelligence Machine learning is a sub field of artificial intelligence. AI is an overarching field of the computer simulating intelligence. Machine learning has become less and less a sub field over time and more a majority of AI. Now we can apply machine learning to vision, speech processing, planning, knowledge representation. This is fast taking over AI. People are beginning to consider the terms artificial intelligence and machine learning synonymous. Self-driving cars are a type of artificial intelligence. The connection between machine learning and self-driving cars is abstract. A fundamental thing in self-driving cars is machine learning. You program the car as to how to fix its mistakes. Another example is facial recognition. The program starts learning about a person’s face over time so it can make an educated guess as to if the person is who they say they are. Once statistics are added then your face can be off by a hair or a hat. Small variations won’t throw it off. How do we start solving the problems we want to be solved? Machine learning has been applied since the 1950s to a broad spectrum of problems. Have to have a little bit of domain knowledge and do some research. Machine Learning Vs Programming Machine learning is any sort of fuzzy programming situation. Programming is when you do things specifically or statically. Why should you care to do machine learning? People should care because this is the next wave of computing. There is a theory that this will displace jobs. Self-driving cars will displace truck drivers, Uber drivers, and taxis. There are things like logo generators already. Machines are generating music, poetry, and website designs. We shouldn’t be afraid that we should keep an eye towards it. If a robot or computer program or AI were able to write its own code, at what point would it be able to overwrite or basically nullify the three laws of robotics? Nick Bostrom wrote the book Superintelligence, which had many big names in technology talking about the dangers of AI. Artificial intelligence has been talked about widely because of the possibility of evil killer robots in the Sci-Fi community. There are people who hold very potential concerns, such as job automation. Consciousness is a huge topic of debate right now on this topic. Is it an emergent property of the human brain? Is what we have with deep learning enough of a representation to achieve consciousness? It is suggested that AI may or may not achieve consciousness. The question is if it is able to achieve consciousness - will we be able to tell there isn’t a person there? If people want to dive into this where do they go? Machine Learning Guide Podcast: http://ocdevel.com/podcasts/machine-learning The Master Algorithm. https://www.amazon.com/Master-Algorithm-Ultimate-Learning-Machine/dp/0465065708 Andrew Ng course: coursera.org/machine/learning Machine Learning Language The main language used for machine learning is Python. This is not because of the language itself, but because of the tools built on top of it. The main framework is TensorFlow. Python in TensorFlow drops to C and executes code on the GPU for performing matrix algebra, which is essential for deep learning. You can always use C, C++, Java, and R. Data scientists mostly use R, while researchers use C and C++ so they can custom code their matrix algebra themselves. Picks Dave: 20-gallon Husky oil free air compressor: http://www.homedepot.com/p/Husky-20-Gal-Vertical-Oil-Free-Electric-Air-Compressor-0332013/207040335 Charles: Twitter T gem: https://rubygems.org/gems/t/versions/2.10.0> Ruby Dev Summit: www.rubydevsummit.com Rake: https://www.sitepoint.com/rake-automate-things/ Tyler: Machine Learning Guide Podcast: http://ocdevel.com/podcasts/machine-learning Philosophy of Mind: Brains, Consciousness, and Thinking Machines (The Great Courses): https://www.amazon.com/Great-Courses-Philosophy-Mind/dp/1598034243

RR 319 Machine Learning with Tyler Renelle This episode of the Ruby Rogues Panel features panelists Charles Max Wood and Dave Kimura. Tyler Renelle, who stops by to talk about machine learning, joins them as a guest. Tyler is the first guest to talk on Adventures in Angular, JavaScript Jabber, and Ruby Rogues. Tune in to find out more about Tyler and machine learning! What is machine learning? Machine learning is a different concept than programmers are used to. There are three phases in computing technology. First phase – building computers in the first place but it was hard coded onto the physical computing machinery Second phase – programmable computers. Where you can reprogram your computer to do anything. This is the phase where programmers fall. Third phase – machine learning falls under this phase. Machine learning is where the computer programs itself to do something. You give the computer a measurement of how it’s doing based on data and it trains itself and learns how to do the task. It is beginning to get a lot of press and become more popular. This is because it is becoming a lot more capable by way of deep learning. AI – Artificial Intelligence Machine learning is a sub field of artificial intelligence. AI is an overarching field of the computer simulating intelligence. Machine learning has become less and less a sub field over time and more a majority of AI. Now we can apply machine learning to vision, speech processing, planning, knowledge representation. This is fast taking over AI. People are beginning to consider the terms artificial intelligence and machine learning synonymous. Self-driving cars are a type of artificial intelligence. The connection between machine learning and self-driving cars is abstract. A fundamental thing in self-driving cars is machine learning. You program the car as to how to fix its mistakes. Another example is facial recognition. The program starts learning about a person’s face over time so it can make an educated guess as to if the person is who they say they are. Once statistics are added then your face can be off by a hair or a hat. Small variations won’t throw it off. How do we start solving the problems we want to be solved? Machine learning has been applied since the 1950s to a broad spectrum of problems. Have to have a little bit of domain knowledge and do some research. Machine Learning Vs Programming Machine learning is any sort of fuzzy programming situation. Programming is when you do things specifically or statically. Why should you care to do machine learning? People should care because this is the next wave of computing. There is a theory that this will displace jobs. Self-driving cars will displace truck drivers, Uber drivers, and taxis. There are things like logo generators already. Machines are generating music, poetry, and website designs. We shouldn’t be afraid that we should keep an eye towards it. If a robot or computer program or AI were able to write its own code, at what point would it be able to overwrite or basically nullify the three laws of robotics? Nick Bostrom wrote the book Superintelligence, which had many big names in technology talking about the dangers of AI. Artificial intelligence has been talked about widely because of the possibility of evil killer robots in the Sci-Fi community. There are people who hold very potential concerns, such as job automation. Consciousness is a huge topic of debate right now on this topic. Is it an emergent property of the human brain? Is what we have with deep learning enough of a representation to achieve consciousness? It is suggested that AI may or may not achieve consciousness. The question is if it is able to achieve consciousness - will we be able to tell there isn’t a person there? If people want to dive into this where do they go? Machine Learning Guide Podcast: http://ocdevel.com/podcasts/machine-learning The Master Algorithm. https://www.amazon.com/Master-Algorithm-Ultimate-Learning-Machine/dp/0465065708 Andrew Ng course: coursera.org/machine/learning Machine Learning Language The main language used for machine learning is Python. This is not because of the language itself, but because of the tools built on top of it. The main framework is TensorFlow. Python in TensorFlow drops to C and executes code on the GPU for performing matrix algebra, which is essential for deep learning. You can always use C, C++, Java, and R. Data scientists mostly use R, while researchers use C and C++ so they can custom code their matrix algebra themselves. Picks Dave: 20-gallon Husky oil free air compressor: http://www.homedepot.com/p/Husky-20-Gal-Vertical-Oil-Free-Electric-Air-Compressor-0332013/207040335 Charles: Twitter T gem: https://rubygems.org/gems/t/versions/2.10.0> Ruby Dev Summit: www.rubydevsummit.com Rake: https://www.sitepoint.com/rake-automate-things/ Tyler: Machine Learning Guide Podcast: http://ocdevel.com/podcasts/machine-learning Philosophy of Mind: Brains, Consciousness, and Thinking Machines (The Great Courses): https://www.amazon.com/Great-Courses-Philosophy-Mind/dp/1598034243

The panelists discuss the Ionic Framework with Max Lynch and Tyler Renelle.

The panelists discuss the Ionic Framework with Max Lynch and Tyler Renelle.

The panelists discuss the Ionic Framework with Max Lynch and Tyler Renelle.

The panelists talk to Tyler Renelle about HabitRPG.

The panelists talk to Tyler Renelle about HabitRPG.

The panelists talk to Tyler Renelle about HabitRPG.

We talked about upcoming events and problems. Professor Dick Smith talked about CSC154 and the upcoming Collegiate Cyber Defense Competition. Tyler ended the meeting talking about Web Development and different systems from web platforms to CMS'.To see the video click here