资源说明：List of tech resources future me and other Javascript/Ruby/Python/Elixir/Elm developers might find useful

# My Tech Resources - James Lavin

## DESCRIPTION

Links to resources I have found useful or think might be helpful to future me or Ruby/Javascript/Python/Erlang/Elixir/Elm developers like me.

## SPECIAL PAGES

After this page grew too large (when Github started truncating it), I split out the following dedicated pages:

* [Books I enjoyed (new page created Nov 2021)](https://github.com/JamesLavin/my_tech_resources/blob/master/Books.markdown)
* [Chinese (not much content because I've been lazy with Chinese)](https://github.com/JamesLavin/my_tech_resources/blob/master/Chinese.markdown)
* [DevOps](https://github.com/JamesLavin/my_tech_resources/blob/master/DevOps.markdown)
* [Elixir](https://github.com/JamesLavin/my_tech_resources/blob/master/Elixir.markdown)
* [Elm](https://github.com/JamesLavin/my_tech_resources/blob/master/Elm.markdown)
* [Event Sourcing](https://github.com/JamesLavin/my_tech_resources/blob/master/EventSourcing.markdown)
* [JavaScript](https://github.com/JamesLavin/my_tech_resources/blob/master/Javascript.markdown)
* [Messaging](https://github.com/JamesLavin/my_tech_resources/blob/master/Messaging.markdown)
* [Python](https://github.com/JamesLavin/my_tech_resources/blob/master/Python.markdown)
* [Ruby](https://github.com/JamesLavin/my_tech_resources/blob/master/Ruby.markdown)

## MAJOR CATEGORIES

[Artificial Intelligence (AI)](#artificial-intelligence-ai) | [Body & Mind](#body--mind) | [Business](#business) | [Clean Code](#clean-code) | [Code Search](#code-search) | [Coffeescript](#javascript---coffeescript) | [CSS](#css) | [Data](#data) | [Databases](#databases) | [Design](#design) | [DevOps](https://github.com/JamesLavin/my_tech_resources/blob/master/DevOps.markdown) | [Domain-Driven Design](https://github.com/JamesLavin/my_tech_resources/blob/master/EventSourcing.markdown#event-sourcing-cqrs-ddd--microservices---domain-driven-design) | [Elasticsearch](#elasticsearch) | [Elixir](https://github.com/JamesLavin/my_tech_resources/blob/master/Elixir.markdown#elixir) | [Elm](https://github.com/JamesLavin/my_tech_resources/blob/master/Elm.markdown#elm) | [Erlang](https://github.com/JamesLavin/my_tech_resources/blob/master/Elixir.markdown#erlang) | [Entrepreneurship](#business---entrepreneurship) | [Event sourcing](https://github.com/JamesLavin/my_tech_resources/blob/master/EventSourcing.markdown#my-event-sourcing--cqrs--ddd--microservice-resources---james-lavin) | [Functional programming](#functional-programming) | [Git](#git) | [Haskell](#haskell) | [Helm](https://github.com/JamesLavin/my_tech_resources#devops---kubernetes---helm) | [HTML5](#html5) | [Istio](https://github.com/JamesLavin/my_tech_resources#devops---istio) | [Javascript](https://github.com/JamesLavin/my_tech_resources/blob/master/Javascript.markdown#javascript) | [Julia](#julia) | [Kafka](https://github.com/JamesLavin/my_tech_resources/blob/master/Messaging.markdown#messaging---kafka) | [Kubernetes](#devops---kubernetes) | [Learning](#learning) | [Linux](#linux) | [Maker movement/ IoT](#maker-movement--internet-of-things-iot) | [Management/Leadership](#management/leadership) | [Messaging](https://github.com/JamesLavin/my_tech_resources/blob/master/Messaging.markdown#messaging) | [Mobile](#mobile) | [MongoDB](#mongodb) | [News](#news) : [programming news](https://github.com/JamesLavin/my_tech_resources#news---programming), [science news](https://github.com/JamesLavin/my_tech_resources#news---science), [tech news](https://github.com/JamesLavin/my_tech_resources#news---tech) | [Node.js](#nodejs) | [Octave](#octave) | [Postgresql](#postgresql) | [Product development](#product-development) | [Productivity  Tools](#productivity-tools) | [Python](https://github.com/JamesLavin/my_tech_resources/blob/master/Python.markdown#python) : [getting started](https://github.com/JamesLavin/my_tech_resources/blob/master/Python.markdown#python---getting-started), [books (free)](https://github.com/JamesLavin/my_tech_resources/blob/master/Python.markdown#python---learning---books-free), [data analysis](https://github.com/JamesLavin/my_tech_resources/blob/master/Python.markdown#python---data-analysis), [learning](https://github.com/JamesLavin/my_tech_resources/blob/master/Python.markdown#python---learning), [Pandas](https://github.com/JamesLavin/my_tech_resources/blob/master/Python.markdown#python---data-analysis---pandas) | [Podcasts](#podcasts) | [R](#r) | [Rails](https://github.com/JamesLavin/my_tech_resources/blob/master/Ruby.markdown#rails) | [Ruby](https://github.com/JamesLavin/my_tech_resources/blob/master/Ruby.markdown#ruby) | [Rust](#rust) | [Scala](#scala) | [Statistical analysis](#statistical-analysis) | [Testing](#testing) | [Tmux](#tmux) | [Usability](#usability) | [Vim](#vim-yeah-its-the-best-though-i-now-use-it-inside-visual-studio-code) | [Visual Studio Code](#visual-studio-code-vscode) | [Web components](#web-components) | [Writing/Publishing](#writingpublishing)

## ALGORITHMS

* [Competitive Programmer’s Handbook - Antti Laaksonen](https://cses.fi/book.pdf)
* Algorithms: Kevin Wayne & Robert Sedgewick (Princeton University): [Part I](https://www.coursera.org/course/algs4partI) & [Part II](https://www.coursera.org/course/algs4partII)
* Algorithms: Design and Analysis - Tim Roughgarden (Stanford University): [Part 1](https://www.coursera.org/course/algo) & [Part 2](https://www.coursera.org/course/algo2)
* [JavaScript Algorithms and Data Structures - Oleksii Trekhleb](https://github.com/trekhleb/javascript-algorithms#readme)
* [Automata: finite automata, context-free grammars, Turing machines, undecidable problems, and intractable problems (NP-completeness) - Jeff Ullman (Stanford University)](https://www.coursera.org/course/automata)
* [Analysis of Algorithms - Robert Sedgewick (Princeton University)](https://www.coursera.org/course/aofa)
* Algorithmic Thinking (Rice University): [Part 1](https://www.coursera.org/learn/algorithmic-thinking-1) & [Part 2](https://www.coursera.org/learn/algorithmic-thinking-2)
* [Algorithmic Toolbox - UC San Diego](https://www.coursera.org/learn/algorithmic-toolbox)
* [Algorithms on Strings - UC San Diego](https://www.coursera.org/learn/algorithms-on-strings)

### ALGORITHMS - CRDTs

* [CRDTS: The Hard Parts - Martin Kleppmann - Hydra distributed computing conference 2020](https://www.youtube.com/watch?v=x7drE24geUw)
* [CRDTs in Production - Dmitry Martyanov](https://www.youtube.com/watch?v=f03FWiIfXoQ)
* [CRDTs: From sequential to concurrent executions - Carlos Baquero Moreno (CodeMesh LDN 2018](https://codesync.global/media/crdts-from-sequential-to-concurrent-executions/)
* [Practical Demystification of CRDTs - Dmitry Ivanov & Nami Nasserazad (Curry On 2016)](https://www.youtube.com/watch?v=ShiU9g5JFq8)
* [Conflict-free Replicated Data Types - Nuno Preguica, Carlos Baquero, and Marc Shapiro [PDF]](https://pages.lip6.fr/Marc.Shapiro/papers/CRDTs-Springer2018-authorversion.pdf)
* [Raft: Understanding Distributed Consensus - TheSecretLivesOfData.com](http://thesecretlivesofdata.com/raft/)

## ANIMATION

* [Algorithms for Animation - Courtney Hemphill](https://youtu.be/GrloJWKBGtg)

## ARTIFICIAL INTELLIGENCE (AI)

* [Fast.ai](http://www.fast.ai/) | [Practical Deep Learning for Coders, v3 (free course)](https://course.fast.ai/videos/?lesson=1) | [The Fast AI Book (free)](https://github.com/fastai/fastbook) | [The Fast AI Book (dead tree)](https://www.amazon.com/Deep-Learning-Coders-fastai-PyTorch/dp/1492045527)
* [Software 2.0 - Andrej Karpathy](https://medium.com/@karpathy/software-2-0-a64152b37c35)
* [Grokking Deep Learning - Andrew Trask](https://github.com/iamtrask/Grokking-Deep-Learning)
* Deep Learning - Ian Goodfellow, Yoshua Bengio, and Aaron Courville (MIT Press): [Chapters](http://www.deeplearningbook.org/) | [Lectures](http://www.deeplearningbook.org/lecture_slides.html) | [Videos - Part 1](https://www.youtube.com/playlist?list=PLsXu9MHQGs8cshZb3YUdtBhcu3LQp0Ax9) | [Videos - Part 2](https://www.youtube.com/playlist?list=PLsXu9MHQGs8fY0IMmV5OAGTdNP4EGwpj1) | [Companion Videos](https://www.youtube.com/playlist?list=PLsXu9MHQGs8df5A4PzQGw-kfviylC-R9b)
* [Siraj Raval's "Artificial Intelligence Education" videos](https://www.youtube.com/channel/UCWN3xxRkmTPmbKwht9FuE5A/playlists)
* [AI School (Microsoft)](https://aischool.microsoft.com/learning-paths)
* [AI and Deep Learning - Two Minute Papers - Károly Zsolnai-Fehér](https://www.youtube.com/playlist?list=PLujxSBD-JXglGL3ERdDOhthD3jTlfudC2) & [Two Minute Papers](https://www.youtube.com/playlist?list=PLujxSBD-JXgnqDD1n-V30pKtp6Q886x7e)
* Andreessen Horowitz: [AI and Deep Learning - Frank Chen](https://a16z.com/2016/06/10/ai-deep-learning-machines/) | [AI: What's Working, What's Not](https://a16z.com/2017/12/07/summit-ai-update-frank-chen/) | [AI Playbook](http://aiplaybook.a16z.com/)
* [12 Amazing Deep Learning Breakthroughs of 2017 - Mariya Yao](https://www.topbots.com/12-amazing-artificial-intelligence-deep-learning-breakthroughs-2017/)
* [Artificial Intelligence in Industry With Dan Faggella (podcast series)](https://itunes.apple.com/us/podcast/artificial-intelligence-in-industry-with-dan-faggella/id670771965)
* [The Code That Runs Our Lives - Geoffrey Hinton](https://www.youtube.com/watch?v=XG-dwZMc7Ng)
* [InfoQ talks](https://www.infoq.com/machinelearning/)
* [Machine Learning (online Coursera class with Stanford professor Andrew Ng)](https://www.coursera.org/learn/machine-learning)
* [Machine Learning (online course from University of Oxford](https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/)
* [Intro to Machine Learning: Pattern Recognition for Fun and Profit - Sebastian Thrun and Katie Malone (Udacity)](https://www.udacity.com/course/intro-to-machine-learning--ud120)
* [Artificial Intelligence (AI) Turns Images & Videos into Gold - Fei-Fei Li](https://www.youtube.com/watch?v=qLCKtc9moks)
* [Artificial Intelligence (AI) invents new knowledge and teaches human new theories - Demis Hassabis](https://www.youtube.com/watch?v=dTGthmNmrK4)
* [Artificial Intelligence (AI) is the Tech Renaissance to Business and Society - Jeff Bezos](https://www.youtube.com/watch?v=0Cy_VOHbXzk)
* [How Will Artificial Intelligence Affect Your Life - Jeff Dean (TEDxLA)](https://www.youtube.com/watch?v=BfDQNrVphLQ)
* [How AI Startups Must Compete with Google - Dr Fei-Fei Li (Google Cloud) & Mike Abbott (KPCB)](https://www.youtube.com/watch?v=Mu3scWZvZKo)
* [Artificial Intelligence is the New Electricity - Andrew Ng (January 2017)](https://www.youtube.com/watch?v=21EiKfQYZXc)
* [How AI detectives are cracking open the black box of deep learning - Science Mag](http://www.sciencemag.org/news/2017/07/how-ai-detectives-are-cracking-open-black-box-deep-learning)
* [Google's Great AI Awakening: We didn't even know we hired the best AI scientists in Google - Eric Schmidt](https://www.youtube.com/watch?v=ynZ8_CFRDgE)
* [Probabilistic Machine Learning and AI - Zoubin Ghahramani](https://www.youtube.com/watch?v=-47G_ULKAHk)
* [Lecture for YC AI - Jeff Dean](https://www.youtube.com/watch?v=HcStlHGpjN8) & [slides](https://blog.ycombinator.com/jeff-deans-lecture-for-yc-ai/)
* [Machines With Brains - Qz.com](https://qz.com/se/machines-with-brains/)
* [The Frontier in Artificial Intelligence (AI): General-Purpose Learning AGI - Mustafa Suleyman](https://www.youtube.com/watch?v=Ui7dLJT5Kp0)
* [Using Machine Learning to Explore Neural Network Architecture - Quoc Le & Barret Zoph (Google Brain team)](https://research.googleblog.com/2017/05/using-machine-learning-to-explore.html)
* [The Compound Effect of Artificial Intelligence (AI) & Silicon-Based Technologies - Steve Jurvetson](https://www.youtube.com/watch?v=n2UU3pOE0WY)
* [How We Teach Computers to Understand Pictures - Fei-Fei Li](https://www.youtube.com/watch?v=40riCqvRoMs)
* [Engineers' Guide to the Artificial Intelligence Galaxy - Kai-Fu Lee Columbia University commencement address](https://www.youtube.com/watch?v=ZXa8G-Z2CCw)
* [The Dark Secret at the Heart of AI - Will Knight](https://www.technologyreview.com/s/604087/the-dark-secret-at-the-heart-of-ai/)
* [AI Expert Kai-Fu Lee, "Don't Miss the Boat of Artificial Intelligence in the Age of AI"](https://www.youtube.com/watch?v=gSgV4P2qpf4)
* [Google's DeepMind CEO: Future & Capabilities of Artificial Intelligence - Demis Hassabis](https://www.youtube.com/watch?v=PSZw8egM2Is)
* [Intro to DeepMind - Juan Silviera (GDD Europe '17)](https://www.youtube.com/watch?v=hzB1SdDvnq8)
* [The Future of Robotics & Artificial Intelligence - Rodney Brooks](http://rodneybrooks.com/forai-future-of-robotics-and-artificial-intelligence/)
* [Amazon Jeff Bezos on Artificial Intelligence (AI), Staffless Store, Self-Driving Car & Donald Trump - Walt Mossberg interview](https://www.youtube.com/watch?v=VAM6b0UkEYw)
* [Large-Scale Deep Learning with TensorFlow for Building Intelligent Systems - Jeff Dean (Google)](https://learning.acm.org/webinar_pdfs/JeffDean_WebinarSlides.pdf)
* [The Future of Artificial Intelligence Documentary 2017](https://www.youtube.com/watch?v=UzT3Tkwx17A)
* [Artificial Intelligence Is Stuck. Here’s How to Move It Forward - Gary Marcus (NY Times)](https://www.nytimes.com/2017/07/29/opinion/sunday/artificial-intelligence-is-stuck-heres-how-to-move-it-forward.html)
* [Half of All Jobs Will Be Replaced by Artificial Intelligence (AI) in 10 Years, AI Expert Kai-Fu Lee](https://www.youtube.com/watch?v=hOZuCdZS7-o)
* [How AI & Computer Vision will Drive our Future - Fei-Fei Li](https://www.youtube.com/watch?v=WHQS35IT75c)
* [Explainable Artificial Intelligence (XAI) - David Gunning (DARPA)](https://www.darpa.mil/program/explainable-artificial-intelligence)
* [International Conference on Learning Representations 2015](https://www.youtube.com/playlist?list=PLhiWXaTdsWB8PnrVZquVyqlRFWXM4ijYz)
* [The Future of Artificial Intelligence - DeepMind CEO Demis Hassabis](https://www.youtube.com/watch?v=4fjmnOQuqao)
* [Google DeepMind: What is it, how does it work and should you be scared? - Sam Shead](http://www.techworld.com/personal-tech/google-deepmind-what-is-it-how-it-works-should-you-be-scared-3615354/)
* [What did AlphaGo do to beat the strongest human Go player? - Tobias Pfeiffer (Full Stack Fest 2016)](https://www.youtube.com/watch?v=b9H9AtbxpPM) | [slides PDF](https://pragtob.files.wordpress.com/2016/09/full_stack_fest.pdf) | [slides Speakerdeck](https://speakerdeck.com/pragtob/what-did-alphago-do-to-beat-the-strongest-human-go-player-1) | [slides Slideshare](http://www.slideshare.net/PragTob/what-did-alphago-do-to-beat-the-strongest-human-go-player)
* [AlphaGo Zero: Learning from scratch - DeepMind](https://deepmind.com/blog/alphago-zero-learning-scratch/)
* [How Does DeepMind's AlphaGo Zero Work? - Siraj Raval](https://www.youtube.com/watch?v=vC66XFoN4DE)
* [Un-Artificial Intelligence - Melinda Seckington (GoRuCo 2015)](https://www.youtube.com/watch?v=7Y1Bv2BJDLs)
* [Neural Networks for Machine Learning - Geoffrey Hinton (University of Toronto)](https://www.coursera.org/course/neuralnets)
* [Artificial Intelligence (online EdX.org class from UC Berkeley)](https://www.edx.org/course/uc-berkeleyx/uc-berkeleyx-cs188-1x-artificial-579)
* [MLOSS.org (Machine Learning Open Source Software)](http://mloss.org/software/)
* [Artificial Stupidity: Adding Smarts to Yer Kode - Randall Thomas](http://www.sdruby.org/podcast/79)
* [Weathering the Data Storm - Claudia Perlich (QConn New York 2014)](http://www.infoq.com/presentations/display-advertising-big-data)

### ARTIFICIAL INTELLIGENCE (AI) - CONVOLUTIONAL NEURAL NETS

* [Feature Visualization: How neural networks build up their understanding of images - Chris Olah, Alexander Mordvintsev, and Ludwig Schubert](https://distill.pub/2017/feature-visualization/)
* [What is wrong with convolutional neural nets? - Geoffrey Hinton](https://www.youtube.com/watch?v=rTawFwUvnLE)
* [How Convolutional Neural Networks Work - Brandon Rohrer](https://www.youtube.com/watch?v=FmpDIaiMIeA)
* [Friendly Introduction to Convolutional Neural Networks and Image Recognition - Luis Serrano](https://www.youtube.com/watch?v=2-Ol7ZB0MmU)
* [Intro to Different Types of Convolutions in Deep Learning - Paul-Louis Pröve](https://medium.com/towards-data-science/types-of-convolutions-in-deep-learning-717013397f4d)
* [Convolutional Neural Networks (TensorFlow)](https://www.tensorflow.org/tutorials/deep_cnn)
* [Chihuahua Or Muffin? Searching for the Best Computer Vision API - Mariya Yao](https://www.topbots.com/comparison-enterprise-image-recognition-computer-vision-api/)
* [pixel-cnn+ - OpenAI](https://github.com/openai/pixel-cnn) & [PixelCNN++: Improving the PixelCNN With Discretized Logistic Mixture Likelihood and Other Modifications](https://arxiv.org/pdf/1701.05517.pdf)
* [A Brief History of CNNs in Image Segmentation: From R-CNN to Mask R-CNN - Dhruv Parthasarathy](https://blog.athelas.com/a-brief-history-of-cnns-in-image-segmentation-from-r-cnn-to-mask-r-cnn-34ea83205de4)
* [Keras Tutorial: The Ultimate Beginner’s Guide to Deep Learning in Python - EliteDataScience.com](https://elitedatascience.com/keras-tutorial-deep-learning-in-python)
* [A Keras multithreaded DataFrame generator for millions of image files - Ryan Woodard](https://techblog.appnexus.com/a-keras-multithreaded-dataframe-generator-for-millions-of-image-files-84d3027f6f43)
* Francois Chollet: [The limitations of deep learning](https://blog.keras.io/the-limitations-of-deep-learning.html) & [The future of deep learning](https://blog.keras.io/the-future-of-deep-learning.html)
* [Deep Neural Networks are Easily Fooled - Evolving AI Lab](https://www.youtube.com/watch?v=M2IebCN9Ht4)
* [CS231n: Convolutional Neural Networks for Visual Recognition - Stanford University](http://cs231n.stanford.edu/)

### ARTIFICIAL INTELLIGENCE (AI) - CAPSULE NETWORKS

* [Capsule Networks: An Improvement to Convolutional Networks - Siraj Raval](https://www.youtube.com/watch?v=VKoLGnq15RM)
* [What is a CapsNet or Capsule Network? - Debarko De](https://hackernoon.com/what-is-a-capsnet-or-capsule-network-2bfbe48769cc)

### ARTIFICIAL INTELLIGENCE (AI) - DEEP NEURAL NETS

* [What do neural networks learn? - Brandon Rohrer](https://www.youtube.com/watch?v=UojVVG4PAG0)
* [Intro to Deep Learning - Alexander Amini (MIT, 2020)](http://introtodeeplearning.com/) | [Lectures](https://www.youtube.com/playlist?list=PLtBw6njQRU-rwp5__7C0oIVt26ZgjG9NI)
* [Intro to Deep Learning with PyTorch - Luis Serrano (Udacity)](https://classroom.udacity.com/courses/ud188)
* [Notes from Coursera Deep Learning courses by Andrew Ng - Tess Ferrandez](https://www.slideshare.net/TessFerrandez/notes-from-coursera-deep-learning-courses-by-andrew-ng)
* [Learn Deep Learning in 6 Weeks - Siraj Raval](https://github.com/llSourcell/Learn_Deep_Learning_in_6_Weeks/)
* [Neural Networks and Deep Learning - Michael Nielsen](http://neuralnetworksanddeeplearning.com/)
* [Advanced Deep Learning & Reinforcement Learning - DeepMind](https://www.youtube.com/playlist?list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs)
* [Mostly Complete Chart of Neural Networks - Fjodor van Veen](https://towardsdatascience.com/the-mostly-complete-chart-of-neural-networks-explained-3fb6f2367464)
* [How Deep Neural Networks Work - Brandon Rohrer](https://www.youtube.com/watch?v=ILsA4nyG7I0)
* [How Neural Networks Really Work - Geoffrey Hinton](https://www.youtube.com/watch?v=EInQoVLg_UY)
* [A friendly introduction to Deep Learning and Neural Networks - Luis Serrano](https://www.youtube.com/watch?v=BR9h47Jtqyw)
* [Deep Learning Demystified - Brandon Rohrer](https://www.youtube.com/watch?v=Q9Z20HCPnww)
* [The Matrix Calculus You Need For Deep Learning - Terence Parr and Jeremy Howard](http://parrt.cs.usfca.edu/doc/matrix-calculus/index.html)
* [Livecoding Madness - Let's Build a Deep Learning Library - Joel Grus](https://www.youtube.com/watch?v=o64FV-ez6Gw)
* [Beyond Backpropagation: Can We Go Deeper Than Deep Learning? - Mariya Yao](https://www.topbots.com/deeper-than-deep-learning-beyond-backpropagation-geoffrey-hinton/)
* [Deep Neural Networks with Tensorboard - Arpan Chakraborty & Luis Serrano (ODSC East 2017)](https://www.youtube.com/watch?v=QVeszB-4Zik) & [Tensorboard demos (Github)](https://github.com/PythonWorkshop/tensorboard_demos)
* [Nuts and Bolts of Applying Deep Learning - Andrew Ng](https://www.youtube.com/watch?v=F1ka6a13S9I)
* [The Deep End of Deep Learning - Hugo Larochelle (TEDxBoston)](https://www.youtube.com/watch?v=dz_jeuWx3j0)
* [Neural Nets for NLP - Graham Neubig (Carnegie Mellon University)](https://www.youtube.com/user/neubig)
* [Friendly Introduction to Deep Learning and Neural Networks](https://www.youtube.com/watch?v=BR9h47Jtqyw)
* [Visualizing and Understanding Deep Neural Networks - Matt Zeiler](https://www.youtube.com/watch?v=ghEmQSxT6tw)
* [The Rise of Artificial Intelligence through Deep Learning - Yoshua Bangio (TEDxMontreal)](https://www.youtube.com/watch?v=uawLjkSI7Mo)

### ARTIFICIAL INTELLIGENCE (AI) - DEEP NEUROEVOLUTION

* [Welcoming the Era of Deep Neuroevolution - Kenneth O. Stanley & Jeff Clune](https://eng.uber.com/deep-neuroevolution/)
* [Why Greatness Cannot Be Planned: The Myth of the Objective - Kenneth Stanley](https://www.youtube.com/watch?v=dXQPL9GooyI)
* [Open-endedness: The last grand challenge you’ve never heard of - Kenneth O. Stanley, Joel Lehman, and Lisa Soros (December 2017)](https://www.oreilly.com/ideas/open-endedness-the-last-grand-challenge-youve-never-heard-of)

### ARTIFICIAL INTELLIGENCE (AI) - FEDERATED LEARNING

* ["Federated learning: private distributed ML" - Mike Lee Williams (StrangeLoop 2019)](https://www.youtube.com/watch?v=VUINeZUAlx8)
* [See: PySyft](https://github.com/JamesLavin/my_tech_resources/blob/master/Python.markdown#python---data-analysis---pysyft)
* [See: TF-Federated]()

### ARTIFICIAL INTELLIGENCE (AI) - GENERAL INTELLIGENCE

* [Is AI Riding a One-Trick Pony? - James Somers](https://www.technologyreview.com/s/608911/is-ai-riding-a-one-trick-pony/)
* [Neuroscience-Inspired Artificial Intelligence - Demis Hassabis, et al. ("Neuron," June 2017)](https://deepmind.com/documents/113/Neuron.pdf)
* [DeepMind’s founder says to build better computer brains, we need to look at our own - James Vincent (The Verge)](https://www.theverge.com/2017/7/19/15998610/ai-neuroscience-machine-learning-deepmind-demis-hassabis-interview)
* [Artificial Intelligence: Turning Our Understanding of the Mind Upside Down - Geoffrey Hinton](https://www.youtube.com/watch?v=fDR1I2Shw_E)
* [Can sensory cortex do backpropagation? - Geoffery Hinton](https://www.youtube.com/watch?v=cBLk5baHbZ8)
* [AI and Neuroscience: A virtuous circle - DeepMind](https://deepmind.com/blog/ai-and-neuroscience-virtuous-circle/)
* [A Path to AI - Yann LeCun](https://www.youtube.com/watch?v=bub58oYJTm0)
* [Creating Human-Level AI - Yoshua Bengio](https://www.youtube.com/watch?v=ZHYXp3gJCaI)
* [Agents that imagine and plan - DeepMind](https://deepmind.com/blog/agents-imagine-and-plan/)
* [DARLA: Improving Zero-Shot Transfer in Reinforcement Learning - Irina Higgins, et al. (2017)](https://arxiv.org/pdf/1707.08475.pdf)
* [When Machines Have Ideas - Ben Vigoda (TEDxBoston)](https://www.youtube.com/watch?v=PCs3vsoMZfY)

### ARTIFICIAL INTELLIGENCE (AI) - GENERATIVE ADVERSARIAL NETWORKS

* [Generative Models - OpenAI](https://blog.openai.com/generative-models/)
* [Generative Adversarial Networks for Style Transfer - Siraj Raval](https://www.youtube.com/watch?v=MgdAe-T8obE)
* [Image Synthesis From Text With Deep Learning | Two Minute Papers #116](https://www.youtube.com/watch?v=rAbhypxs1qQ)
* [Amazon has an algorithm that designs clothes by replicating human creativity - Qz.com](https://qz.com/1062257/amazons-new-ai-algorithm-designs-clothes-without-human-designers/)

### ARTIFICIAL INTELLIGENCE (AI) - GOOGLE APIS

* [Machine Learning APIs by Example - Sara Robinson (Google I/O '17)](https://www.youtube.com/watch?v=ETeeSYMGZn0)

### ARTIFICIAL INTELLIGENCE (AI) - HARDWARE

* [Tesla is working with AMD to develop its own A.I. chip for self-driving cars, says source - Jordan Novet](https://www.cnbc.com/2017/09/20/tesla-building-an-ai-chip-for-its-cars-with-amd-globalfoundries.html)
* [First demonstration of brain-inspired device to power artificial systems - University of Southampton](https://www.southampton.ac.uk/news/2016/09/memristor-brain.page)
* [Machine Learning Infrastructure - TechEmergence.com](https://www.techemergence.com/category/industries/ml-infrastructure/)

### ARTIFICIAL INTELLIGENCE (AI) - H2O.AI

* [H2O.ai](https://www.h2o.ai/)

### ARTIFICIAL INTELLIGENCE (AI) - HIERARCHICAL TEMPORAL MEMORY (HTM)

* [The Biological Path Towards Strong AI - Matt Taylor (StrangeLoop 2017)](https://www.youtube.com/watch?v=-h-cz7yY-G8)
* [HTM Youtube Channel - Numenta](https://www.youtube.com/user/OfficialNumenta/playlists)
* [Numenta.org](https://numenta.org/)

### ARTIFICIAL INTELLIGENCE (AI) - JAX: AUTOGRAD AND XLA

"Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more"

* [Github.com/Google/JAX](https://github.com/Google/jax)
* [JAX As Accelerated NumPy - Rosalia Schneider & Vladimir Mikulik](https://colab.research.google.com/github/google/jax/blob/master/docs/jax-101/01-jax-basics.ipynb)
* [Introduction to Graph Neural Nets with JAX/jraph - Lisa Wang & Nikola Jovanović](https://colab.research.google.com/github/deepmind/educational/blob/master/colabs/summer_schools/intro_to_graph_nets_tutorial_with_jraph.ipynb)

### ARTIFICIAL INTELLIGENCE (AI) - KERAS

* [TensorFlow, Keras and deep learning, without a PhD - Martin Gorner](https://codelabs.developers.google.com/codelabs/cloud-tensorflow-mnist/?linkId=71247707#0)
* [The Keras Blog - Francois Chollet](https://blog.keras.io/)
* [Keras: Multiple outputs and multiple losses - Adrian Rosebrock](https://www.pyimagesearch.com/2018/06/04/keras-multiple-outputs-and-multiple-losses/)
* Keras.js: [Github](https://github.com/transcranial/keras-js) | [Demos](https://transcranial.github.io/keras-js/#/) | [Docs](https://transcranial.github.io/keras-js-docs/)
* [First Contact With Deep Learning: Practical Introduction with Keras - Jordi Torres](https://torres.ai/first-contact-deep-learning-practical-introduction-keras/)
* [Intro to text classification with Keras: automatically tagging Stack Overflow posts - Sara Robinson, Josh Gordon, and Marianne Linhares Monteiro](https://cloud.google.com/blog/big-data/2017/10/intro-to-text-classification-with-keras-automatically-tagging-stack-overflow-posts)
* [Problem-solving with ML: automatic document classification - Ahmed Kachkach](https://cloud.google.com/blog/big-data/2018/01/problem-solving-with-ml-automatic-document-classification)

### ARTIFICIAL INTELLIGENCE (AI) - LINEAR ALGEBRA

* [All the Linear Algebra You Need for AI - Rachel Thomas](https://github.com/fastai/fastai/blob/master/tutorials/linalg_pytorch.ipynb)
* [MATH - LINEAR ALGEBRA](https://github.com/JamesLavin/my_tech_resources#math---linear-algebra)

### ARTIFICIAL INTELLIGENCE (AI) - MACHINE LEARNING

* [Machine Learning Cheatsheets - Stanford CS 229](https://github.com/afshinea/stanford-cs-229-machine-learning)
* [End-to-End Machine Learning - Brandon Rohrer](https://brohrer.github.io/blog.html)
* [Papers With Code - Hottest AI/ML papers with associated code](https://paperswithcode.com/)
* [arXiv.org machine learning articles](https://arxiv.org/list/stat.ML/recent)
* [Machine Learning from Scratch - Erik Linder-Norén](https://github.com/eriklindernoren/ML-From-Scratch)
* [Rules of Machine Learning: Best Practices for ML Engineering - Martin Zinkevich](http://martin.zinkevich.org/rules_of_ml/rules_of_ml.pdf)
* [Machine Learning Mastery](https://machinelearningmastery.com/start-here/)
* [Jupyter notebooks for the book "Hands-on Machine Learning with Scikit-Learn and TensorFlow" - Aurélien Geron](https://github.com/ageron/handson-ml)
* [Jupyter notebooks for the book "Deep Learning With Python Notebooks" - François Chollet](https://github.com/fchollet/deep-learning-with-python-notebooks)
* [This Week in Machine Learning](https://medium.com/@david.joyner)
* ["Deep Thinking" - Demis Hassabis interviews Garry Kasparov (Talks at Google)](https://www.youtube.com/watch?v=zhkTHkIZJEc)
* [What Is Machine Learning? - Luis Serrano](https://www.youtube.com/watch?v=IpGxLWOIZy4)
* [CS229: Machine Learning - Andrew Ng (Stanford University)](https://see.stanford.edu/Course/CS229)

#### ARTIFICIAL INTELLIGENCE (AI) - MACHINE LEARNING - MLOPS

* [What Is MLOps? - NVIDIA](https://blogs.nvidia.com/blog/2020/09/03/what-is-mlops/)
* [MLOps: Continuous delivery and automation pipelines in machine learning - Google Cloud](https://cloud.google.com/solutions/machine-learning/mlops-continuous-delivery-and-automation-pipelines-in-machine-learning)
* [MLOps vs. AIOps - SeattleDataGuy](https://medium.com/better-programming/mlops-vs-aiops-6e5354704dab)

### ARTIFICIAL INTELLIGENCE (AI) - NATURAL LANGUAGE PROCESSING (NLP)

* [Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition, 3rd ed](https://web.stanford.edu/~jurafsky/slp3/https://web.stanford.edu/~jurafsky/slp3/) | [Jan 2022 PDF](https://web.stanford.edu/~jurafsky/slp3/ed3book_jan122022.pdf)
* [NLP-progress; Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks - Sebastian Ruder](https://github.com/sebastianruder/nlp-progress) | [NlPProgress.com](https://nlpprogress.com/)
* [The New Era in NLP - Rachel Thomas (SciPy 2019)](https://www.youtube.com/watch?v=KChtdexd5Jo)
* [NLP Highlights (podcast) - Matt Gardner, Pradeep Dasigi, and Waleed Ammar](https://soundcloud.com/nlp-highlights)
* [Natural Language Processing with Deep Learning (Stanford University, Winter 2017)](https://www.youtube.com/playlist?list=PL3FW7Lu3i5Jsnh1rnUwq_TcylNr7EkRe6) | [2019 course](http://web.stanford.edu/class/cs224n/)
* [Exploring Transfer Learning with T5: the Text-To-Text Transfer Transformer - Google](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) | [Text-to-Text Transfer Transformer (T5)](https://github.com/google-research/text-to-text-transfer-transformer) | [Colossal, Cleaned Crawled Corpus (C4)](https://www.tensorflow.org/datasets/catalog/c4)
* [Oxford Deep NLP 2017 course](https://github.com/oxford-cs-deepnlp-2017/lectures)
* [NLP Newsletter - Democratizing Artificial Intelligence Research, Education, and Technologies](https://medium.com/@ibelmopan)
* [High Performance Natural Language Processing - Gabriel Ilharco, et al. (EMNLP 2020)](https://slideslive.com/38940826) | [Slides (PDF)](http://gabrielilharco.com/publications/EMNLP_2020_Tutorial__High_Performance_NLP.pdf)
* Speech and Language Processing, 3rd ed draft, Daniel Jurafsky and James H. Martin: [PDF](https://web.stanford.edu/~jurafsky/slp3/ed3book.pdf) | [Webpage](https://web.stanford.edu/~jurafsky/slp3/)
* [Natural Language Processing - Jacob Eisenstein](https://github.com/jacobeisenstein/gt-nlp-class/raw/master/notes/eisenstein-nlp-notes.pdf)
* [Deep Learning for NLP - Ed Grefenstette (DeepMind)](https://www.youtube.com/watch?v=Y95JwaynE40)
* [KDNuggets NLP](https://www.kdnuggets.com/?s=NLP)
* [Text Analytics Techniques](http://ai.intelligentonlinetools.com/ml/)
* [NLP For Hackers](https://nlpforhackers.io/)
* [NLP Newsletter - Sebastian Ruder](http://newsletter.ruder.io/)
* [Sebastian Ruder blog](http://ruder.io/)
* [4 Approaches to Natural Language Processing & Understanding - Maria Yao](https://www.topbots.com/4-different-approaches-natural-language-processing-understanding/)
* [Stanford Natural Language Processing Group](https://nlp.stanford.edu/) | [CoreNLP](https://stanfordnlp.github.io/CoreNLP/)
* [Sebastian Ruder blog](http://ruder.io/#open)
* [NLP - MachineLearningPlus.com](https://www.machinelearningplus.com/nlp/)
* [Problem-solving with ML: automatic document classification - Ahmed Kachkack](https://cloud.google.com/blog/big-data/2018/01/problem-solving-with-ml-automatic-document-classification)
* [GuidedLDA: Guided Topic modeling with latent Dirichlet allocation - Vikash Singh](https://github.com/vi3k6i5/guidedlda) & [How our startup switched from Unsupervised LDA to Semi-Supervised GuidedLDA - Vikash Singh](https://medium.freecodecamp.org/how-we-changed-unsupervised-lda-to-semi-supervised-guidedlda-e36a95f3a164)
* [NLP in R: Topic Modelling - Rachael Tatman](https://www.kaggle.com/rtatman/nlp-in-r-topic-modelling/code)
* [NLP For Topic Modeling & Summarization Of Legal Documents - Oguejiofor Chibueze](https://towardsdatascience.com/nlp-for-topic-modeling-summarization-of-legal-documents-8c89393b1534)
* [Spooky NLP and Topic Modelling tutorial - Anisotropic](https://www.kaggle.com/arthurtok/spooky-nlp-and-topic-modelling-tutorial/code)
* [natural: general natural language facilities for node](https://github.com/NaturalNode/natural)

#### ARTIFICIAL INTELLIGENCE (AI) - NATURAL LANGUAGE PROCESSING (NLP) - ALLEN NLP

* [AllenNLP](https://github.com/allenai/allennlp)

#### ARTIFICIAL INTELLIGENCE (AI) - NATURAL LANGUAGE PROCESSING (NLP) - GENSIM

* Gensim: [Website](https://radimrehurek.com/gensim/) | [Tutorials](https://radimrehurek.com/gensim/tutorial.html) | [API docs](https://radimrehurek.com/gensim/apiref.html) | [Github](https://github.com/RaRe-Technologies/gensim) | [Tutorials](https://github.com/RaRe-Technologies/gensim/blob/develop/tutorials.md#tutorials)
* [gensim-data](https://github.com/RaRe-Technologies/gensim-data)
* [Complete Guide to Topic Modeling with Scikit-Learn and Gensim - George-Bogdan Ivanov](https://nlpforhackers.io/topic-modeling/)

#### ARTIFICIAL INTELLIGENCE (AI) - NATURAL LANGUAGE PROCESSING (NLP) - OPENNLP

* Apache OpenNLP: [Homepage](http://opennlp.apache.org/) | [Github](https://github.com/apache/opennlp)
* [An Anatomy of an Answer: Open NLP & Discourse Analysis-Based Indexing - Boris Galitsky (ApacheCon @Home 2020)](https://www.youtube.com/watch?v=-0xwb7szKnQ) (starts after 6 1/2 minutes)

#### ARTIFICIAL INTELLIGENCE (AI) - NATURAL LANGUAGE PROCESSING (NLP) - SPACY

* spaCy: Industrial-strength Natural Language Processing (NLP) with Python and Cython: [Github](https://github.com/explosion/spaCy) | [Spacy.io](https://spacy.io/)
* [spaCy cheatsheet - DataCamp](http://datacamp-community-prod.s3.amazonaws.com/29aa28bf-570a-4965-8f54-d6a541ae4e06)

#### ARTIFICIAL INTELLIGENCE (AI) - NATURAL LANGUAGE PROCESSING (NLP) - TEXTACY

* [Textacy](https://github.com/chartbeat-labs/textacy)

### ARTIFICIAL INTELLIGENCE (AI) - NEWS

* [Chipin](https://www.chipin.com/artificial-intelligence/)
* [Distill.pub](https://distill.pub/)
* [Futurism](https://futurism.com/artificialintelligence/)
* [Google](https://ai.google/)
* [HackerNoon.com](https://hackernoon.com/tagged/ai)
* [Import AI Newsletter - Jack Clark](http://us13.campaign-archive1.com/home/?u=67bd06787e84d73db24fb0aa5&id=6c9d98ff2c)
* [Kate Crawford](https://twitter.com/katecrawford)
* [Machine Learnings](https://machinelearnings.co/)
* [Marketing Artificial Intelligence Network](https://www.marketingaiinstitute.com/blog)
* [The Next Web](https://thenextweb.com/artificial-intelligence/#.tnw_urviI0GS)
* [Open AI](https://blog.openai.com/)
* [Quartz - Dave Gershgorn](https://qz.com/author/dgershgornqz/)
* [The Register](http://www.theregister.co.uk/emergent_tech/artificial_intelligence/)
* [Science](http://search.sciencemag.org/?q=artificial%20intelligence)
* Tech Emergence: [Guides](https://www.techemergence.com/category/primary-content-type/guides/) | [Research](https://www.techemergence.com/category/primary-content-type/research/) | [Expert Interviews](https://www.techemergence.com/category/expert-interviews/) | [Companies](https://www.techemergence.com/companies/)
* [This Week in Machine Learning & AI](https://twimlai.com/blog/)
* [Topbots - Mariya Yao](https://www.topbots.com/author/mariya/) & [Forbes](https://www.forbes.com/sites/mariyayao/people/mariyayao/#4d2c1d1e3dae)
* [VentureBeat](https://venturebeat.com/category/ai/)
* [Wired - Tom Simonite](https://www.wired.com/author/tom-simonite/)

### ARTIFICIAL INTELLIGENCE (AI) - OPEN AI

* [OpenAI Gym](https://gym.openai.com/) | [Github](https://github.com/openai/gym)

### ARTIFICIAL INTELLIGENCE (AI) - OPTIMIZATION

* [Deep Learning as a Mixed Convex-Combinatorial Optimization Problem - Abram L. Friesen and Pedro Domingos](https://arxiv.org/pdf/1710.11573.pdf)

### ARTIFICIAL INTELLIGENCE (AI) - PODCASTS

* [Artificial Intelligence in Industry](https://www.techemergence.com/category/primary-content-type/artificial-intelligence-podcast/)
* [Lex Fridman Podcast: AI](https://lexfridman.com/ai/)
* [Machine Learning Guide - Tyler Renelle](http://ocdevel.com/podcasts/machine-learning)
* [Practical AI](https://www.podcastrepublic.net/podcast/1406537385)
* [Talking Machines](http://www.thetalkingmachines.com/episodes)
* [This Week in Machine Learning & AI](https://twimlai.com/shows/)

### ARTIFICIAL INTELLIGENCE (AI) - PYTHON

* [5 Genius Python Deep Learning Libraries - EliteDataScience.com](https://elitedatascience.com/python-deep-learning-libraries)

#### ARTIFICIAL INTELLIGENCE (AI) - PYTHON - PYTORCH

* [Github](https://github.com/pytorch/pytorch) | [Pytorch.org](http://pytorch.org/)
* ML/DL for Everyone With PyTorch - Sung Kim: [Videos](https://www.youtube.com/playlist?list=PLlMkM4tgfjnJ3I-dbhO9JTw7gNty6o_2m) & [Slides](https://drive.google.com/drive/folders/0B41Zbb4c8HVyUndGdGdJSXd5d3M)
* [Introducing Pytorch for fast.ai](http://www.fast.ai/2017/09/08/introducing-pytorch-for-fastai/)
* [PyTorchZeroToAll](https://drive.google.com/drive/folders/0B41Zbb4c8HVyUndGdGdJSXd5d3M)
* [PyTorch vs TensorFlow — spotting the difference - Kirill Dubovikov](https://medium.com/towards-data-science/pytorch-vs-tensorflow-spotting-the-difference-25c75777377b)

### ARTIFICIAL INTELLIGENCE (AI) - QUANTUM AI

* [Quantum AI: The Next Frontier (Applied AI Conference 2017)](https://www.youtube.com/watch?v=DGTv-rVGb_M)

### ARTIFICIAL INTELLIGENCE (AI) - REINFORCEMENT LEARNING

* [Reinforcement Learning: An Introduction, 2nd ed (in progress - complete draft)- Richard S. Sutton & Andrew G. Barto](http://incompleteideas.net/sutton/book/bookdraft2017nov5.pdf)
* [A Brief Survey of Deep Reinforcement Learning - Kai Arulkumaran, Marc Peter Deisenroth, Miles Brundage, Anil Anthony Bharath](https://arxiv.org/pdf/1708.05866.pdf)
* [Elon Musk’s A.I. Destroys Champion Gamer! - ColdFusion](https://www.youtube.com/watch?v=XbDmxEOj9OY)
* [How Does DeepMind's AlphaGo Zero Work? - Siraj Raval](https://www.youtube.com/watch?v=vC66XFoN4DE)
* [Human-level control through Deep Reinforcement Learning - Deep Mind](https://deepmind.com/research/dqn/)
* [Deep Q Learning for Video Games - The Math of Intelligence #9 - Siraj Raval](https://www.youtube.com/watch?v=79pmNdyxEGo)
* [Teaching a Neural Network to play a game using Q-learning - Soren D](https://www.practicalai.io/teaching-a-neural-network-to-play-a-game-with-q-learning/)

### ARTIFICIAL INTELLIGENCE (AI) - SEQUENCE MODELS (RNN, LSTM, GRM)

* [A friendly introduction to Recurrent Neural Networks - Luis Serrano](https://www.youtube.com/watch?v=UNmqTiOnRfg)
* [Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) - Brandon Rohrer](https://www.youtube.com/watch?v=WCUNPb-5EYI)
* [Automated Image Captioning with ConvNets and Recurrent Nets - Andrej Karpathy & Fei-Fei Li (Center for Brains, Minds and Machines, Stanford University)](https://www.youtube.com/watch?v=yk6XDFm3J2c&t=762)
* [Introduction to LSTMs in Tensorflow - Harini Suresh and Nicholas Locascio (MIT Center for Brains, Minds + Machines)](https://www.youtube.com/watch?v=l4X-kZjl1gs) & [Tensorflow code (LSTM Sentiment Classifier)](https://github.com/nicholaslocascio/bcs-lstm)
* [Recurrent Neural Networks (TensorFlow)](https://www.tensorflow.org/tutorials/recurrent)
* [LSTM Networks - The Math of Intelligence - Siraj Raval](https://www.youtube.com/watch?v=9zhrxE5PQgY)
* [Sequence-to-Sequence Models (TensorFlow)](https://www.tensorflow.org/tutorials/seq2seq)

### ARTIFICIAL INTELLIGENCE (AI) - REAL-WORLD EXAMPLES

* [Google’s voice-generating AI is now indistinguishable from humans - Dave Gershgorn](https://qz.com/1165775/googles-voice-generating-ai-is-now-indistinguishable-from-humans/)
* [AlphaZero: DeepMind's New Chess AI | Two Minute Papers #216](https://www.youtube.com/watch?v=2ciR6rA85tg)
* [CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning - Stanford ML Group](https://stanfordmlgroup.github.io/projects/chexnet/)
* [Artificial intelligence goes deep to beat humans at poker - Tonya Riley (Science)](http://www.sciencemag.org/news/2017/03/artificial-intelligence-goes-deep-beat-humans-poker) & [How an AI took down four world-class poker pros - Chris Valazco (Engadget)](https://www.engadget.com/2017/02/10/libratus-ai-poker-winner/)
* [The AI Race - Australian Broadcasting Corporation](https://www.youtube.com/watch?v=gLeuCj0ZFo4)
* [Google's Learning Software Learns to Write Learning Software - Tom Simonite (Wired)](https://www.wired.com/story/googles-learning-software-learns-to-write-learning-software)
* [Meet Spot, the robot dog that can run, hop and open doors - Marc Raibert (TED Talk 2017)](https://www.youtube.com/watch?v=AO4In7d6X-c)
* [A new t-shirt sewing robot can make as many shirts per hour as 17 factory workers - Marc Bain](https://qz.com/1064679/a-new-t-shirt-sewing-robot-can-make-as-many-shirts-per-hour-as-17-factory-workers/)
* [How computers learn to recognize objects instantly - Joseph Redmon (TED Talk 2017)](https://www.youtube.com/watch?v=Cgxsv1riJhI)
* [The ultimate promise of artificial intelligence lies in sorting cucumbers - Dave Gershgorn](https://qz.com/771921/the-ultimate-promise-of-artificial-intelligence-lies-in-sorting-cucumbers/)
* [Google’s speech recognition is now almost as accurate as humans - 9-to-5 Google](https://9to5google.com/2017/06/01/google-speech-recognition-humans/)
* [Using Machine Learning to predict parking difficulty - James Cook, et al. (Google)](https://research.googleblog.com/2017/02/using-machine-learning-to-predict.html)
* [A.I. is Progressing Faster Than You Think - ColdFusion](https://www.youtube.com/watch?v=mQO2PcEW9BY)
* [The era of easily faked, AI-generated photos is quickly emerging - Dave Gershgorn](https://qz.com/1115353/new-research-from-nvidia-shows-that-the-era-of-easily-faked-ai-generated-photos-is-quickly-emerging/)
* [Artificial intelligence is great at predicting the size of hurricanes, but humans still need to figure out their impact - Dave Gershgorn](https://qz.com/1072215/artificial-intelligence-is-great-at-predicting-the-size-of-hurricanes-but-humans-still-need-to-figure-out-their-impact/)
* [Voyage's first self-driving car deployment](https://news.voyage.auto/voyages-first-self-driving-car-deployment-29c7688c6a1)
* [The world’s best Dota 2 players just got destroyed by a killer AI from Elon Musk’s startup - T.C. Sottek (The Verge)](https://www.theverge.com/2017/8/11/16137388/dota-2-dendi-open-ai-elon-musk)
* [Revisiting the Effectiveness of Off-the-shelf Temporal Modeling Approaches for Large-scale Video Classification - Yunlong Bian et al.](https://arxiv.org/pdf/1708.03805.pdf) | [Activity-Net.org](http://activity-net.org/)
* [Microsoft Dynamics 365 now offers service chatbots as part of AI push](https://venturebeat.com/2017/09/25/microsoft-dynamics-365-customers-get-service-chatbots-as-part-of-ai-push/)
* [Automated Crowdturfing Attacks and Defenses in Online Review Systems - Yuanshun Yao, et al.(2017)](https://arxiv.org/pdf/1708.08151.pdf)
* [A.I. Experiments: Visualizing High-Dimensional Space - Google Developers](https://www.youtube.com/watch?v=wvsE8jm1GzE)
* [Facebook’s Language-Creating AI Bots Are Now Required to Negotiate in English - Futurism](https://futurism.com/facebooks-language-creating-ai-bots-are-now-required-to-negotiate-in-english/) | [Facebook Shut Down AI After It Invented Its Own Language](http://www.theepochtimes.com/n3/2274480-facebook-shut-down-ai-after-it-invented-its-own-language/)
* [AI learns from professional gamers — then crushes them - Peter Holley (Washington Post)](http://www.bendbulletin.com/business/5521413-151/ai-learns-from-professional-gamers-then-crushes)
* [Google Has Started Adding Imagination to Its DeepMind AI - ScienceAlert.com](https://www.sciencealert.com/google-has-started-adding-imagination-to-its-deepmind-ai) & [Imagination-Augmented Agents for Deep Reinforcement Learning - DeepMind](https://arxiv.org/pdf/1707.06203.pdf)
* [Two Minute Papers](https://www.youtube.com/channel/UCbfYPyITQ-7l4upoX8nvctg)
* [Twitter taught Microsoft’s AI chatbot to be a racist asshole in less than a day - James Vincent](https://www.theverge.com/2016/3/24/11297050/tay-microsoft-chatbot-racist)
* [These AI bots are so believable, they get asked out on dates (CNBC)](https://www.cnbc.com/2017/07/27/these-ai-bots-are-so-believable-they-get-asked-out-on-dates.html)
* [TensorKart: Self-driving MarioKart with TensorFlow - Kevin Hughes](https://kevinhughes.ca/blog/tensor-kart)
* [Artificial Intelligence (AI) Software and Robots are Replacing White-Collar Workers](https://www.youtube.com/watch?v=31IOoZ5c_9c)
* [Baidu Deep Voice explained: Part 1 — the Inference Pipeline](https://blog.athelas.com/paper-1-baidus-deep-voice-675a323705df)
* [Google's Deep Mind Explained! - Self-Learning A.I. - ColdFusion](https://www.youtube.com/watch?v=TnUYcTuZJpM)
* [Nvidia Lets You Peer Inside the Black Box of Its Self-Driving AI - Will Knight](https://www.technologyreview.com/s/604324/nvidia-lets-you-peer-inside-the-black-box-of-its-self-driving-ai/)
* [The incredible inventions of intuitive AI - Maurice Conti (TED Talks)](https://www.youtube.com/watch?v=aR5N2Jl8k14)
* [AI Experiments: Explore machine learning in simple, hands-on ways (Google)](https://experiments.withgoogle.com/ai)
* [An internet company has found a single manager for 60,000 employees - Dave Gershgorn (Quartz)](https://qz.com/se/machines-with-brains/1017298/rainforest-qa-manages-its-60000-remote-employees-exclusively-through-a-series-of-algorithms/)
* [How Google is making music with artificial intelligence (Science)](http://www.sciencemag.org/news/2017/08/how-google-making-music-artificial-intelligence)
* [Chinese chatbots apparently re-educated after political faux pas](http://www.reuters.com/article/us-china-robots-idUSKBN1AK0G1)
* [Mark Sagar Made a Baby in His Lab. Now It Plays the Piano](https://www.bloomberg.com/news/features/2017-09-07/this-startup-is-making-virtual-people-who-look-and-act-impossibly-real)
* [IBM Watson: Smartest Machine Ever Built Documentary (NOVA)](https://www.youtube.com/watch?v=3zQI-LMcDnA)
* [BuzzFeed News Trained A Computer To Search For Hidden Spy Planes. This Is What We Found](https://www.buzzfeed.com/peteraldhous/hidden-spy-planes)
* [Maybe the A.I. dystopia is already here - Anne Applebaum (Washington Post)](https://www.washingtonpost.com/opinions/global-opinions/maybe-the-ai-dystopia-is-already-here/2017/07/28/d0b4c8ae-7392-11e7-8f39-eeb7d3a2d304_story.html)
* [How PayPal Is Taking a Chance on AI to Fight Fraud - American Banker](https://www.americanbanker.com/news/how-paypal-is-taking-a-chance-on-ai-to-fight-fraud)
* [China's big bet on domination in AI is no longer a long shot (National Post)](http://nationalpost.com/news/world/chinas-big-bet-on-domination-in-ai-is-no-longer-a-long-shot/wcm/07026820-58d0-4b91-a084-a49d177b009c)
* [A.I. Learns Nobel Prize Experiment in Just 1 Hour! - ColdFusion](https://www.youtube.com/watch?v=lJcGzmsLRUo)
* [Goldman Sacked: How Artificial Intelligence Will Transform Wall Street - Newsweek](http://www.newsweek.com/2017/03/10/how-artificial-intelligence-transform-wall-street-560637.html)
* [The Rise of the Artificially Intelligent Hedge Fund - Wired](https://www.wired.com/2016/01/the-rise-of-the-artificially-intelligent-hedge-fund/)
* [The Robots Are Coming for Wall Street - Nathaniel Popper (NY Times)](https://www.nytimes.com/2016/02/28/magazine/the-robots-are-coming-for-wall-street.html)
* [Neural Networks for Language and Understanding - Geoff Hinton](https://www.youtube.com/watch?v=o8otywnWwKc)
* [Researchers built an invisible backdoor to hack AI’s decisions - Dave Gershgorn (qz.com)](https://qz.com/1061560/researchers-built-an-invisible-back-door-to-hack-ais-decisions/)

#### ARTIFICIAL INTELLIGENCE (AI) - REAL-WORLD EXAMPLES - HEALTHCARE

* [Heart Disease Diagnosis with Deep Learning - Chuck-Hou Yee](https://blog.insightdatascience.com/heart-disease-diagnosis-with-deep-learning-c2d92c27e730)
* [Deep Learning in Medical Imaging - Ben Glocker (#reworkDL)](https://www.youtube.com/watch?v=2_Jv11VpOF4)
* [Deep Learning for Predicting Glioblastoma Subtypes from MRI. Peter Chang, MD](https://www.youtube.com/watch?v=LVJbvK_HAbY)
* [Defining a Patient Population With Cirrhosis: An Automated Algorithm With Natural Language Processing - E.K. Chang, et al., Journal of Clinical Gastroenterology 2016](https://www.ncbi.nlm.nih.gov/pubmed/27348317)
* [Predictive Analytics, NLP Flag Psychosis with 100% Accuracy - Jennifer Bresnick (Health IT Analytics, 2015)](https://healthitanalytics.com/news/predictive-analytics-nlp-flag-psychosis-with-100-accuracy)
* [Chinese robot dentist is first to fit implants in patient’s mouth without any human involvement - Alice Yan](http://www.scmp.com/news/china/article/2112197/chinese-robot-dentist-first-fit-implants-patients-mouth-without-any-human)
* [Case Study: TensorFlow in Medicine - Retinal Imaging - Lily Peng (TensorFlow Dev Summit 2017)](https://www.youtube.com/watch?v=oOeZ7IgEN4o)
* [Artificial intelligence can diagnose prostate cancer as well as a pathologist](https://sciencebusiness.net/healthy-measures/news/artificial-intelligence-can-diagnose-prostate-cancer-well-pathologist)
* [Better Medicine Through Machine Learning - Suchi Saria (TEDxBoston)](https://www.youtube.com/watch?v=Nj2YSLPn6OY)
* [Efficient identification of nationally mandated reportable cancer cases using natural language processing and machine learning - John D Osborne, et al. (Journal of Informatics in Health and Biomedicine, 2016)](https://academic.oup.com/jamia/article/23/6/1077/2399248/Efficient-identification-of-nationally-mandated)
* [IBM CEO: "Watson AI will change everything in Healthcare. Radiologists will lose jobs soon"](https://www.youtube.com/watch?v=YkEYuoa_ooo)
* [IBM pitched its Watson supercomputer as a revolution in cancer care. It’s nowhere close - Casey Ross & Ike Swetlitz (STAT)](https://www.statnews.com/2017/09/05/watson-ibm-cancer/) vs. [IBM CEO: "Watson AI will change everything in Healthcare. Radiologists will lose jobs soon"](https://www.youtube.com/watch?v=YkEYuoa_ooo)
* [Machine Learning in Health Care - Antonio Criminisi](https://www.youtube.com/watch?v=XQsHPuXKmO4)
* [Big Data and Machine Learning in Healthcare: How, Why, and When - Dr. Leonard D'Avolio (HIMSS Big Data and Analytics Conference)](https://www.youtube.com/watch?v=kqdfkkAdwxw)
* [Epic to use NLP to aid documentation, decision support](https://www.healthdatamanagement.com/news/epic-to-use-nlp-to-aid-documentation-decision-support)
* [AI can detect Alzheimer's 10 years before symptoms show up - Mariella Moon](https://www.engadget.com/2017/09/17/ai-alzheimers-early-detection/)

### ARTIFICIAL INTELLIGENCE (AI) - SIMULATION

* [Running Programs In Reverse for Deeper A.I. - Zenna Tavares](https://www.youtube.com/watch?v=JnonBxKKZsg)

### ARTIFICIAL INTELLIGENCE (AI) - SUPERINTELLIGENCE

* [Myths and Facts About Superintelligent AI (With MIT's Max Tegmark) - minutephysics](https://www.youtube.com/watch?v=3Om9ssTm194)
* [Not If, But How Artificial Intelligence Might Take Over the World - Hugh Baillie](https://www.youtube.com/watch?v=mDMP2t6lUjo)
* [Artificial Intelligence: it will kill us - Jay Tuck (TEDxHamburgSalon)](https://www.youtube.com/watch?v=BrNs0M77Pd4)

### ARTIFICIAL INTELLIGENCE (AI) - TENSORFLOW

* [Awesome-Tensorflow (curated list of resources)](https://github.com/jtoy/awesome-tensorflow)
* [Github](https://github.com/tensorflow/tensorflow) | [Installing](https://github.com/tensorflow/tensorflow) | [Website](https://www.tensorflow.org/) | [Youtube](https://www.youtube.com/channel/UC0rqucBdTuFTjJiefW5t-IQ) | [Udacity course](https://www.udacity.com/course/deep-learning--ud730) | [Stanford course](https://web.stanford.edu/class/cs20si) | [Examples](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/examples)
* [Machine Learning with TensorFlow - Andrew Gasparovic (GDD Europe '17)](https://www.youtube.com/watch?v=2zWSr-3gkWY)
* [TensorFlow in 5 Minutes - Siraj Raval](https://www.youtube.com/watch?v=2FmcHiLCwTU)
* [Effective TensorFlow for Non-Experts - Martin Wicke (Google I/O '17)](https://www.youtube.com/watch?v=5DknTFbcGVM)
* [Intro to TensorFlow - Alejandro Solano (EuroPython 2017)](https://ep2017.europython.eu/media/conference/slides/introduction-to-tensorflow.pdf)
* [Tensorflow and Deep Learning Without a PhD - Martin Görner](https://www.youtube.com/watch?v=vq2nnJ4g6N0)
* [TensorFlow Tutorial For Beginners - Karlijn Willems](https://www.datacamp.com/community/tutorials/tensorflow-tutorial#gs.x6XtYOU)
* [TensorFlow Dev Summit 2017](https://www.youtube.com/watch?v=mWl45NkFBOc&list=PLOU2XLYxmsIKGc_NBoIhTn2Qhraji53cv)
* [TensorFlow at DeepMind - Daniel Visentin (TensorFlow Dev Summit 2017)](https://www.youtube.com/watch?v=VdDmhOCw6J0)
* [TensorFlow Wide & Deep Learning Tutorial (TensorFlow)](https://www.tensorflow.org/tutorials/wide_and_deep)

#### ARTIFICIAL INTELLIGENCE (AI) - TENSORFLOW - FEDERATED

* [TensorFlow-Federated](https://www.tensorflow.org/federated)

#### ARTIFICIAL INTELLIGENCE (AI) - TENSORFLOW - HOROVOD

* [Horovod: Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet](https://github.com/horovod/horovod)

#### ARTIFICIAL INTELLIGENCE (AI) - TENSORFLOW - KUBEFLOW

* [KubeFlow: Machine Learning Toolkit for Kubernetes](https://www.kubeflow.org/)
* [Data Science on Steroids with Kubeflow - Markus Bauer & Sascha Grunert](https://medium.com/@saschagrunert/data-science-on-steroids-with-kubeflow-60fc3ba92b06)
* [Machine Learning Frameworks on Kubernetes](https://github.com/aws-samples/machine-learning-using-k8s)
* [Kubeflow: Portable Machine Learning on Kubernetes - Michelle Casbon (@Scale 2018)](https://www.youtube.com/watch?v=JCBJNuDvsuw)
* [kfctl](https://github.com/kubeflow/kubeflow/tree/master/kfctl)

#### ARTIFICIAL INTELLIGENCE (AI) - TENSORFLOW - MOBILE

* [TensorFlow.js](https://js.tensorflow.org/) | [Tutorials](https://js.tensorflow.org/tutorials/) | [Docs](https://js.tensorflow.org/api/0.10.0/) | [Examples](https://github.com/tensorflow/tfjs-examples)
* [On-device machine learning: TensorFlow on Android - Yufeng Guo (Google Cloud Next '17)](https://www.youtube.com/watch?v=EnFyneRScQ8)

### ARTIFICIAL INTELLIGENCE (AI) - UNSUPERVISED LEARNING

* [The Next Frontier in AI: Unsupervised Learning - Yann LeCun](https://www.youtube.com/watch?v=IbjF5VjniVE)

### ARTIFICIAL INTELLIGENCE (AI) - VIDEOS

* [AI By the Bay 2017](https://www.youtube.com/playlist?list=PLNESult6cnOk3Q8tjfSIWy49Fz37l0wZU)
* [Cognifest NYC 2017](https://www.youtube.com/playlist?list=PLNESult6cnOnwQuvT8LaRihdLYcTgKLov)

### ARTIFICIAL INTELLIGENCE (AI) - WEBSITES

* [Insight Data Science](https://blog.insightdatascience.com/)
* [KD Nuggets](http://www.kdnuggets.com/)

## ASDF

* [asdf - Version manager for Ruby, Node.js, Elixir, Erlang & more](https://github.com/asdf-vm/asdf) | [Docs](https://asdf-vm.com/#/core-manage-asdf-vm)
* [Agnostic Version Management With asdf - Bobby Grayson](https://elixirschool.com/blog/asdf-version-management/)

## BLOCKCHAINS

* [Blockchain: The Slowest (and most Fascinating) Database in the World - Stefan Tilkov (GOTO Amsterdam 2017)](https://www.youtube.com/watch?v=li3rfBAP_fE)
* [What the #?!\* is Bitcoin? - Jeremy Rubin (TEDxBeaconStreet)](https://www.youtube.com/watch?v=Vzjtvt77mgc)
* [Blockchain Disruption: How Bitcoin Technology Creates a Sharing Economy - Thomas Ramge (TEDxHamburg)](https://www.youtube.com/watch?v=ZF0iCdYkXTM)

### BLOCKCHAINS - BITCOIN

* [Ten years in, nobody has come up with a use for blockchain - Kai Stinchcombe](https://hackernoon.com/ten-years-in-nobody-has-come-up-with-a-use-case-for-blockchain-ee98c180100)
* [Bitcoin -- distributing power & trust - Eric Spano (TEDxConcordia)](https://www.youtube.com/watch?v=WI1pbHi1fww)

## BODY & MIND

* [How to Stay Healthy as a Programmer - Florian](https://codinginflow.com/healthy-programmer)
* [Possibly The Best Way To Be A Great Programmer: Be Brain-Healthy!! - Jon Davis](https://dzone.com/articles/possibly-the-best-way-to-be-a-)
* [Seven Tips for the Healthy Programmer - Bart Jacobs](https://code.tutsplus.com/articles/seven-tips-for-the-healthy-programmer--cms-25043)
* [Tips on Staying Fit for Software Developers - Asahi Technologies](https://www.asahitechnologies.com/blog/tips-on-staying-fit-for-software-developers/)
* [5 Hacks to Effortlessly Build Healthy Habits in 2018 - Steve](https://www.nerdfitness.com/blog/how-to-build-healthy-habits-that-stick/)

### BODY & MIND - BURNOUT

* [Depression and Burnout: the Hardest Refactor I’ve ever done - Jérôme Petazzoni (GOTO 2019)](https://www.youtube.com/watch?v=m20KBFUuw-w)

### BODY & MIND - CORONAVIRUS

* [Coronavirus Is A PANDEMIC.... Technically - Dr Mikhail Varshavski](https://www.youtube.com/watch?v=Xl2nA_xuHjY)
* [Preparing for Coronavirus to Strike the U.S. - Zeynep Tufekci (Scientific American)](https://blogs.scientificamerican.com/observations/preparing-for-coronavirus-to-strike-the-u-s/)
* [Dr. John Campbell](https://www.youtube.com/watch?v=5rOTz9duXwo) & [other Dr. John Campbell videos](https://www.youtube.com/user/Campbellteaching/videos)
* [What you need to know as coronavirus outbreak reaches "decisive point" - CBS News](https://www.youtube.com/watch?v=Ihjw3cKfWFA)
* [Coronavirus Do’s And Don’ts: What You Need To Know To Protect Your Family - TODAY](https://www.youtube.com/watch?v=2UGgBGff8H8)
* [How coronavirus spreads and what you can do to prevent it - CBS News](https://www.youtube.com/watch?v=NYWNdHYz10E) & [You’re Likely to Get the Coronavirus: Most cases are not life-threatening, which is also what makes the virus a historic challenge to contain - Dr James Hamblin (The Atlantic)](https://www.theatlantic.com/health/archive/2020/02/covid-vaccine/607000/)
* [How Coronavirus Kills: Acute Respiratory Distress Syndrome (ARDS) & Treatment - Pulmonologist Dr. Roger Seheult](https://www.youtube.com/watch?v=okg7uq_HrhQ)
* [Coronavirus Epidemic: Updates, Spread, Symptoms, & Treatment (COVID-19) - MedCram](https://www.youtube.com/watch?v=quDYb_x54DM&list=PLQ_IRFkDInv_zLVFTgXA8tW0Mf1iiuuM_&index=30&t=0s)
* [Coronavirus: How the deadly epidemic sparked a global emergency | Four Corners (Australian Broadcast Corporation)](https://www.abc.net.au/4corners/coronavirus/11996398) | [Youtube](https://www.youtube.com/watch?v=ycrqXJYf1SU)
* [Coronavirus - Dr Mike Hansen](https://www.youtube.com/watch?v=-h_MWGPOyOE&list=PLgqCliyXQhezro4JBt2zJDWo7XdCTn_45&index=9)
* [Coronavirus outbreak: U.S. braces for rise in COVID-19 cases as WHO raises threat to "highest level" - Global National](https://www.youtube.com/watch?v=F_Jq7ItdHtA)
* [Spanish Flu: a warning from history - Cambridge University](https://www.youtube.com/watch?v=3x1aLAw_xkY)
* [How coronavirus (Covid-19) spread day by day - Channel 4 News (Australia)](https://www.youtube.com/watch?v=Zl0V-OhZYk4)
* [Coronavirus disease (COVID-19) outbreak - World Health Organization (WHO)](https://www.who.int/emergencies/diseases/novel-coronavirus-2019)

### BODY & MIND - EXERCISE

* [The 25 Most Significant Health Benefits of Physical Activity and Exercise - Len Kravitz](http://www.unm.edu/~lkravitz/Article%20folder/healthbenefitsaa.html)

### BODY & MIND - INTERMITTENT FASTING

* [The Beginner’s Guide to Intermittent Fasting - James Clear](https://jamesclear.com/the-beginners-guide-to-intermittent-fasting)
* [Intermittent fasting: Surprising update - Monique Tello, MD, MPH](https://www.health.harvard.edu/blog/intermittent-fasting-surprising-update-2018062914156)
* [Intermittent fasting: No advantage over conventional weight loss diets - German Cancer Research Center (Deutsches Krebsforschungszentrum, DKFZ)](https://www.sciencedaily.com/releases/2018/11/181126115842.htm)
* [Intermittent Fasting Made My Life Easier, and Happier - Larissa Zimberoff (NY Times)](https://www.nytimes.com/2019/06/04/well/eat/intermittent-fasting-made-my-life-easier-and-happier.html)
* [Intermittent Fasting: Is it Right for You? - Jane Racey Gleeson](https://healthblog.uofmhealth.org/wellness-prevention/intermittent-fasting-it-right-for-you)
* [Does Intermittent Fasting Work? - Monica Reinagel, MS, LD/N, CNS](https://www.quickanddirtytips.com/health-fitness/weight-loss/does-intermittent-fasting-work)
* [The Leangains Guide - Martin Berkhan](https://leangains.com/the-leangains-guide)

### BODY & MIND - PODCASTS

* [Ask a Harvard Professor](https://ask-a-harvard-professor.simplecast.com/episodes)
* [Brain Science with Ginger Campbell, MD](https://brainsciencepodcast.com/)
* [Brain Science: Neuroscience & Behavior](https://podcasts.apple.com/sa/podcast/brain-science-neuroscience-behavior/id1475672610)
* [BrainStuff](https://podcasts.apple.com/us/podcast/brainstuff/id260335249)
* [Do The Thing - Melissa Urban](https://podcasts.apple.com/us/podcast/do-the-thing-with-whole30s-melissa-urban/id1460152081)
* [Hidden Brain - NPR](https://podcasts.apple.com/us/podcast/hidden-brain/id1028908750)
* [Love Your Work - David Kadavy](https://podcasts.apple.com/us/podcast/love-your-work/id1067860103)
* [The Moment - Brian Koppelman](https://podcasts.apple.com/us/podcast/the-moment-with-brian-koppelman/id814550071)

### BODY & MIND - POSTURE

* [Back Pain & Sitting](https://www.youtube.com/playlist?list=PL8l32k1r15l4Y2rO_fDZtgnnZoWwoeXzf) & [More Bob (Schrupp) & Brad (Heineck)](https://www.youtube.com/channel/UCmTe0LsfEbpkDpgrxKAWbRA)

### BODY & MIND - SLEEP

* [Programmers and sleep - David Zych](https://davidzych.com/programmers-and-sleep/)
* [You Need More Than 6 Hours of Sleep - Gret Yeutter](https://hackernoon.com/you-need-more-than-6-hours-of-sleep-5186cfcf1dd5)

### BODY & MIND - STOICISM

* [The philosophy of Stoicism - Massimo Pigliucci](https://www.youtube.com/watch?v=R9OCA6UFE-0)
* [Epictetus - How To Be A Stoic (Stoicism)](https://www.youtube.com/watch?v=wH6dSe_dYgM)
* [Stoicism as a philosophy for an ordinary life - Massimo Pigliucci (TEDxAthens)](https://www.youtube.com/watch?v=Yhn1Fe8cT)

## BOOKS

* [Mind-Expanding-Books - Vishnu Ks](https://github.com/hackerkid/Mind-Expanding-Books)
* [List of free programming books (many languages)](https://github.com/vhf/free-programming-books/blob/master/free-programming-books.md)
* [List of free programming books - CodeInfo.info](http://isn.codelab.info/ressources/livres-numeriques/free-programming-books/)

## BROWSERS

### BROWSERS - APIS

* [WebExtensions](https://developer.mozilla.org/en-US/Add-ons/WebExtensions)
* [JavaScript APIs](https://developer.mozilla.org/en-US/Add-ons/WebExtensions/API)
* [Tabs](https://developer.mozilla.org/en-US/Add-ons/WebExtensions/API/tabs)

### BROWSERS - AUTOMATION

* [Nightmare](https://github.com/segmentio/nightmare)
* [Phantom.js](http://phantomjs.org/)
* [Selenium](http://docs.seleniumhq.org/)

### BROWSERS - BEAKER BROWSER

* [Beaker Browser - Peer-to-peer browser with tools to create and host websites](https://beakerbrowser.com/)
* [IPFS.io - Peer-to-peer hypermedia protocol to make the web faster, safer, and more open](https://ipfs.io/)
* [Dat Project - Data-sharing protocol for applications of the future](https://datproject.org/)

### BROWSERS - CHROME

* [DevTools](https://developers.google.com/web/tools/chrome-devtools/)
* [Web.dev - Google](https://web.dev/)
* [Lighthouse: Automated tool for improving the quality of web pages](https://developers.google.com/web/tools/lighthouse/)
* [Puppeteer: Most things you can do manually in the browser can be done using Puppeteer](https://github.com/GoogleChrome/puppeteer)
* [Workbox: JavaScript libraries for adding offline support (service workers, asset caching, etc.) to web apps](https://developers.google.com/web/tools/workbox/)

### BROWSERS - PLUGINS/EXTENSIONS

#### BROWSERS - PLUGINS/EXTENSIONS - CHROME

* [Documentation](https://developer.chrome.com/extensions) | [Extensions APIs](https://developer.chrome.com/extensions/api_index) | [Overview](https://developer.chrome.com/extensions/overview) | [Examples](https://developer.chrome.com/extensions/samples) | [CodeLab](https://developer.chrome.com/apps/app_codelab_intro) | [Developer's Guide](https://developer.chrome.com/extensions/devguide)
* [Javascript APIs](https://developer.chrome.com/extensions/api_index)
* [How to Make a Chrome Extension - Gabe Berke-Williams](https://robots.thoughtbot.com/how-to-make-a-chrome-extension)
* [Create a Google Chrome Extension (For Beginners) - iEatWebsites](https://www.youtube.com/watch?v=uV4L-wcnK3Y)
* [Extensionizr: Start a Chrome extension in 15 seconds](http://extensionizr.com)

#### BROWSERS - PLUGINS/EXTENSIONS - FIREFOX

* [WebExtensions](https://developer.mozilla.org/en-US/docs/Mozilla/Add-ons/WebExtensions)
    * [Your first extension](https://developer.mozilla.or

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