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
- A Return to Machine Learning 🌈
- A Visual Introduction to Machine Learning 🌈
- Machine Learning is Fun!
- Deep Reinforcement Learning: Pong from Pixels 🌈
- Inside Libratus, the Poker AI That Out-Bluffed the Best Humans
- Machine Learning in Javascript: Introduction
- Realtime control of sequence generation with character based Long Short Term Memory Recurrent Neural Networks 😅
- Why is machine learning 'hard'?
- Unreasonable effectiveness of RNNs 😅
- colah's blog
- Machine Learning Website with many Tutorial of Machine Learning :rainbow:
- Beginners tutorial for decision tree implementation 🌈
- Machine Learning Beginner tutorial Supervised and Unsupervised Learning 🌈
- Q-Learning Tutorial 😅
- Big O notation Free Code Camp
- Ray Wenderlich Big O notation
- Interview Cake Big O notation
- Youtube Video Big O notation Derek Banas
- Youtube Video for Big O notation HackerRank
- Random Forest in Python 😅
- CreativeAI - On the Democratisation & Escalation of Creativity 🌈
- Reducing the Dimensionality of Data with Neural Networks
- Learning Deep Architectures for AI
- Let’s code a Neural Network from scratch (Processing) 😅
- Distill - Demystifying Machine Learning Research
- Machine Learning in Javascript 😅
- A.I. Experiments from google
- Rohan & Lenny #3: Recurrent Neural Networks & LSTMs 😅
- Backpropogating an LSTM: A Numerical Example 😅
- Naive Bayes for Dummies; A Simple Explanation
- Machine Learning Crash Course @ Berkeley
- How to approach almost any ML problem? 😅
- Technical Notes on ML & AI by Chris Albon 😅
- Naive Bayes and Text Classification 😅
- First Contact With TensorFlow 😅
- Machine Learning for Designers by Patrick Hebron, Accompanying Webcast: Machine learning and the future of design
- Machine Learning Book 🌈
- A first encounter with machine learning
- Natural Language Processing with Python 😅
- A Brief Introduction to Neural Networks 😅
- Machine Learning Crash Course By Google
- Coursera - Machine Learning with TensorFlow on GCP 😅
- The Neural Aesthetic @ SchoolOfMa, Summer 2016 🌈
- Machine Learning for Musicians and Artists, Kadenze[Scheduled course] 🌈
- Creative Applications of Deep Learning with TensorFlow, Kadenze[Whole Program] 🌈 😅
- Coursera - Machine Learning
- Coursera - Neural Networks 😅
- Practical Deep Learning for Coders
- Course in Machine Learning
- Stanford Course Machine Learning
- Udacity - Machine Learning Engineer[Whole Program] 😅
- DeepMind - Reinforcement Learning lectures by David Silver
- A Deep Q Reinforcement Learning Demo
- How to use Q Learning in Video Games Easily 🌈
- K-nearest
- The Infinite Drum Machine 🌈
- Visualizing various ML algorithms 🌈
- Image-to-Image - from lines to cats 🌈
- Recurrent Neural Network Tutorial for Artists 🌈
- Browser Self-Driving Car,Learning to Drive Blog Post
- The Neural Network Zoo (cheat sheet of nn architectures)
- Slice of Machine Learning
- Bidirectional LSTM for IMDB sentiment classification 😅
- Land Lines
- nnvis - Topological Visualisation of a Convolutional Neural Network 🌈
- char-rnn A character level language model (a fancy text generator) 🌈 😅
- Machine Learning Projects
- Reinforcement Learning
- Evolutionary Algorithms
- Deep Learning
- Video Lectures of Deep Learning :sweat_smile:
- Neural networks class - Université de Sherbrooke
- A Friendly Introduction to Machine Learning :bowtie:
- A friendly introduction to Deep Learning and Neural Networks :bowtie:
- A friendly introduction to Convolutional Neural Networks and Image Recognition :bowtie:
- Deep Learning Demystified :bowtie:
- How Deep Neural Networks Work :bowtie:
- How Convolutional Neural Networks work
- Artificial Intelligence
- MIT 6.034 Artificial Intelligence, Fall 2010 - Complete set of course lectures
- Awesome Machine Learning
- QA StackOverflow Machine Learning Algorithms
- Free dataset for projects
- Facial Recognition Database
- 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
- Machine Learning Resources
- Isochrones using the Google Maps Distance Matrix API
- Index of Best AI/Machine Learning Resources
- ConvNetJS - Javascript library for training Deep Learning models (Neural Networks) 😅
- RecurrentJS - Deep Recurrent Neural Networks and LSTMs in Javascript 😅
- AIXIjs - JavaScript demo for running General Reinforcement Learning (RL) agents 😅
- WORD2VEC 😅
- Neuro.js
- Google Chrome Extensión to download all Image of the Google Search 🌈
1 Scikit-Learn
- Projector 😅
- Magenta 🌈
- TensorFlow and Flask, Thanks to @Hebali basic pipeline, minus TensorFlow plus a very basic placeholder function
- Awesome Tensorflow - curated list of TensorFlow tutorials