Examples and experiments around ML for upcoming Coding Train videos and ITP course.

Since resources across the internet vary in terms of their pre-requisites and general accessibility, it is useful to give attributes to them so that it is easy to understand where a resource fits into the wider machine learning scope. Below is a few suggested attributes (please extend):

• 🌈 = creative
• = beginner
• 😅 = intermediate, some pre-requisites
• = advanced, many pre-requisites

• Articles & Posts
• Books
• Courses
• Examples
• Projects
• Videos
• Resources
• Newsletter
• Tools
  • Tensorflow
  • t-SNE

1. A Return to Machine Learning 🌈
2. A Visual Introduction to Machine Learning 🌈
3. Machine Learning is Fun!
4. Deep Reinforcement Learning: Pong from Pixels 🌈
5. Inside Libratus, the Poker AI That Out-Bluffed the Best Humans
6. Machine Learning in Javascript: Introduction
7. Realtime control of sequence generation with character based Long Short Term Memory Recurrent Neural Networks 😅
8. Why is machine learning 'hard'?
9. Unreasonable effectiveness of RNNs 😅
10. colah's blog
11. ‪Machine Learning Website with many Tutorial of Machine Learning‪ ‬:rainbow:
12. Beginners tutorial for decision tree implementation 🌈‪
13. Machine Learning Beginner tutorial Supervised and Unsupervised Learning 🌈‪
14. Q-Learning Tutorial 😅
15. Big O notation Free Code Camp
16. Ray Wenderlich Big O notation
17. Interview Cake Big O notation
18. Youtube Video Big O notation Derek Banas
19. Youtube Video for Big O notation HackerRank
20. Random Forest in Python 😅
21. CreativeAI - On the Democratisation & Escalation of Creativity 🌈
22. Reducing the Dimensionality of Data with Neural Networks
23. Learning Deep Architectures for AI
24. Let’s code a Neural Network from scratch (Processing) 😅
25. Distill - Demystifying Machine Learning Research
26. Machine Learning in Javascript 😅
27. A.I. Experiments from google
28. Rohan & Lenny #3: Recurrent Neural Networks & LSTMs 😅
29. Backpropogating an LSTM: A Numerical Example 😅
30. Naive Bayes for Dummies; A Simple Explanation
31. Machine Learning Crash Course @ Berkeley
32. How to approach almost any ML problem? 😅
33. Technical Notes on ML & AI by Chris Albon 😅
34. Naive Bayes and Text Classification 😅
35. First Contact With TensorFlow 😅

1. Machine Learning for Designers by Patrick Hebron, Accompanying Webcast: Machine learning and the future of design
2. Machine Learning Book 🌈
3. A first encounter with machine learning
4. Natural Language Processing with Python 😅
5. A Brief Introduction to Neural Networks 😅

1. Machine Learning Crash Course By Google
2. Coursera - Machine Learning with TensorFlow on GCP 😅
3. The Neural Aesthetic @ SchoolOfMa, Summer 2016 🌈
4. Machine Learning for Musicians and Artists, Kadenze[Scheduled course] 🌈
5. Creative Applications of Deep Learning with TensorFlow, Kadenze[Whole Program] 🌈 😅
6. Coursera - Machine Learning
7. Coursera - Neural Networks 😅
8. Practical Deep Learning for Coders
9. ‪Course in Machine Learning
10. ‪Stanford Course Machine Learning
11. Udacity - Machine Learning Engineer[Whole Program] 😅
12. DeepMind - Reinforcement Learning lectures by David Silver

1. A Deep Q Reinforcement Learning Demo
2. How to use Q Learning in Video Games Easily 🌈
3. K-nearest
4. The Infinite Drum Machine 🌈
5. Visualizing various ML algorithms 🌈
6. Image-to-Image - from lines to cats 🌈
7. Recurrent Neural Network Tutorial for Artists 🌈
8. Browser Self-Driving Car,Learning to Drive Blog Post
9. The Neural Network Zoo (cheat sheet of nn architectures)
10. Slice of Machine Learning

1. Bidirectional LSTM for IMDB sentiment classification 😅
2. Land Lines
3. nnvis - Topological Visualisation of a Convolutional Neural Network 🌈
4. char-rnn A character level language model (a fancy text generator) 🌈 😅
5. Machine Learning Projects

• Reinforcement Learning
  1. Artificial Intelligence in Google's Dinosaur (English Sub)
  2. How to use Q Learning in Video Games Easily
• Evolutionary Algorithms
  1. Evolving Swimming Soft-Bodied Creatures 🌈
  2. Harnessing evolutionary creativity: evolving soft-bodied animats in simulated physical environments 🌈
  3. Reproduce image with genetic algorithm
• Deep Learning
  1. ‪Video Lectures of Deep Learning‪ ‬:sweat_smile:
  2. Neural networks class - Université de Sherbrooke
  3. ‪A Friendly Introduction to Machine Learning‪ ‬:bowtie:
  4. ‪A friendly introduction to Deep Learning and Neural Networks ‬:bowtie:
  5. ‪A friendly introduction to Convolutional Neural Networks and Image Recognition ‬:bowtie:
  6. ‪Deep Learning Demystified ‬:bowtie:
  7. ‪How Deep Neural Networks Work ‬:bowtie:
  8. ‪How Convolutional Neural Networks work
• Artificial Intelligence
  1. MIT 6.034 Artificial Intelligence, Fall 2010 - Complete set of course lectures

1. Awesome Machine Learning
2. ‪QA StackOverflow Machine Learning Algorithms
3. ‪Free dataset for projects
4. Facial Recognition Database
5. iOS application- Read top articles for your professional skills with @mybridge - Here you can find new articles every day for Data Science and Machine Learning among other things
6. Machine Learning Resources
7. Isochrones using the Google Maps Distance Matrix API
8. Index of Best AI/Machine Learning Resources

1. Data Science
2. Data Elixir
3. Artificial Intelligence Weekly
4. Data Aspirant

1. ConvNetJS - Javascript library for training Deep Learning models (Neural Networks) 😅
2. RecurrentJS - Deep Recurrent Neural Networks and LSTMs in Javascript 😅
3. AIXIjs - JavaScript demo for running General Reinforcement Learning (RL) agents 😅
4. WORD2VEC 😅
5. Neuro.js
6. ‪Google Chrome Extensión to download all Image of the Google Search 🌈 1 Scikit-Learn

1. Projector 😅
2. Magenta 🌈
3. TensorFlow and Flask, Thanks to @Hebali basic pipeline, minus TensorFlow plus a very basic placeholder function
4. Awesome Tensorflow - curated list of TensorFlow tutorials

1. Big deep learning news: Google Tensorflow chooses Keras
2. Simple end-to-end TensorFlow examples
3. TensorFlow website Getting Started

1. t-SNE 😅
2. t-SNE 😅
3. An illustrated introduction to the t-SNE algorithm
4. Visualizing Data Using t-SNE 🌈