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JSJ 278 Machine Learning with Tyler Renelle

JavaScript Jabber

Stay current on JavaScript, Node, and Front-End development. Learn from experts in programming, careers, and technology every week. Become a supporter of this podcast: <a href="https://www.spreaker.com/podcast/javascript-jabber--6102064/support?utm_source=rss&utm_medium=rss&utm_campaign=rss">https://www.spreaker.com/podcast/javascript-jabber--6102064/support</a>.

<a href="https://ctt.ec/ZwO15" target="_blank" rel="noreferrer noopener">Tweet this Episode</a>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:<ul><li>Whether machine learning will replace programming jobs</li><li>Economic automation</li><li>Which platforms and languages to use to get into machine learning</li><li>and much, much more...</li></ul>Links:<ul><li><a href="https://www.raspberrypi.org/" target="_blank" rel="noreferrer noopener">Raspberry Pi</a></li><li><a href="https://www.arduino.cc/" target="_blank" rel="noreferrer noopener">Arduino</a></li><li><a href="http://news.ycombinator.com" target="_blank" rel="noreferrer noopener">Hacker News</a></li><li><a href="https://en.wikipedia.org/wiki/Artificial_neural_network" target="_blank" rel="noreferrer noopener">Neural Networks (wikipedia)</a></li><li><a href="https://deepmind.com/" target="_blank" rel="noreferrer noopener">Deep Mind</a></li><li>Shallow Algorithms</li><li><a href="https://en.wikipedia.org/wiki/Genetic_algorithm" target="_blank" rel="noreferrer noopener">Genetic Algorithms</a></li><li><a href="https://en.wikipedia.org/wiki/CRISPR" target="_blank" rel="noreferrer noopener">Crisper gene editing</a></li><li><a href="http://wix.com" target="_blank" rel="noreferrer noopener">Wix</a></li><li><a href="https://thegrid.io/" target="_blank" rel="noreferrer noopener">thegrid.io</a></li><li><a href="http://codeschool.com" target="_blank" rel="noreferrer noopener">Codeschool</a></li><li><a href="http://codecademy.com" target="_blank" rel="noreferrer noopener">Codecademy</a></li><li><a href="https://www.tensorflow.org/" target="_blank" rel="noreferrer noopener">Tensorflow</a></li><li><a href="https://keras.io/" target="_blank" rel="noreferrer noopener">Keras</a></li><li><a href="http://ocdevel.com/podcasts/machine-learning" target="_blank" rel="noreferrer noopener">Machine Learning Guide</a></li><li><a href="https://www.coursera.org/learn/machine-learning" target="_blank" rel="noreferrer noopener">Andrew Ng Coursera Course</a></li><li><a href="http://python.org" target="_blank" rel="noreferrer noopener">Python</a></li><li><a href="https://www.r-project.org/" target="_blank" rel="noreferrer noopener">R</a></li><li><a href="https://www.java.com/en/" target="_blank" rel="noreferrer noopener">Java</a></li><li><a href="http://torch.ch/" target="_blank" rel="noreferrer noopener">Torch</a></li><li><a href="http://pytorch.org/" target="_blank" rel="noreferrer noopener">PyTorch</a></li><li><a href="http://caffe.berkeleyvision.org/" target="_blank" rel="noreferrer noopener">Caffe</a></li><li><a href="http://scikit-learn.org/stable/" target="_blank" rel="noreferrer noopener">Scikit learn</a></li><li><a href="http://pytorch.org/" target="_blank" rel="noreferrer noopener">Tensorfire</a></li><li><a href="https://pair-code.github.io/deeplearnjs/" target="_blank" rel="noreferrer noopener">DeepLearn.js</a></li><li><a href="http://amzn.to/2xRXDIU" target="_blank" rel="noreferrer noopener">The Singularity is Near by Ray Kurzweil</a></li><li><a href="https://github.com/reinforceio/tensorforce" target="_blank" rel="noreferrer noopener">Tensorforce</a></li><li><a href="http://amzn.to/2fBvhrG" target="_blank" rel="noreferrer noopener">Super Intelligence by Nick Bostrom</a></li></ul>Picks:Aimee<ul><li><a href="http://include-media.com/" target="_blank" rel="noreferrer noopener">Include media</a></li><li><a href="http://nodevember.org/" target="_blank" rel="noreferrer noopener">Nodevember</a></li><li><a href="https://fidgets-hub.myshopify.com/collections/phone-cases" target="_blank" rel="noreferrer noopener">Phone cases</a></li></ul>AJ<ul><li><a href="http://dataskeptic.com" target="_blank" rel="noreferrer noopener">Data Skeptic</a></li><li><a href="http://amzn.to/2yrnqVn" target="_blank" rel="noreferrer noopener">Ready Player One</a></li></ul>Joe<ul><li><a href="http://amzn.to/2yeXT0E" target="_blank" rel="noreferrer noopener">Everybody Lies</a></li></ul>Tyler<ul><li><a href="http://www.imdb.com/title/tt0470752/" target="_blank" rel="noreferrer noopener">Ex Machina</a></li><li><a href="http://amzn.to/2jNYDYj" target="_blank" rel="noreferrer noopener">Philosophy of Mind: Brains, Consciousness, and Thinking Machines</a></li></ul>Special Guest: Tyler Renelle. Support this podcast at — <a href="https://redcircle.com/javascript-jabber/donations" target="_blank" rel="noreferrer noopener">https://redcircle.com/javascript-jabber/donations</a> Privacy & Opt-Out: <a href="https://redcircle.com/privacy" target="_blank" rel="noreferrer noopener">https://redcircle.com/privacy</a> Become a supporter of this podcast: <a href="https://www.spreaker.com/podcast/javascript-jabber--6102064/support?utm_source=rss&utm_medium=rss&utm_campaign=rss">https://www.spreaker.com/podcast/javascript-jabber--6102064/support</a>.

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JSJ 278 Machine Learning with Tyler Renelle

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