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72 changes: 43 additions & 29 deletions README.md
Original file line number Diff line number Diff line change
@@ -1,6 +1,16 @@
# Machine-Learning
Examples and experiments around ML for upcoming Coding Train videos and ITP course.

# Resource attributes

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):

- :rainbow: = creative
- :bowtie: = beginner
- :sweat_smile: = intermediate, some pre-requisites
- :godmode: = advanced, many pre-requisites

# Table of Contents
<!-- MarkdownTOC depth=4 -->
- [Articles & Posts](#articles--posts)
Expand All @@ -14,53 +24,57 @@ Examples and experiments around ML for upcoming Coding Train videos and ITP cour

<!-- /MarkdownTOC -->
## Articles & Posts
1. [A Return to Machine Learning](https://medium.com/@kcimc/a-return-to-machine-learning-2de3728558eb#.vlqnbo9yg)
1. [A Visual Introduction to Machine Learning](http://www.r2d3.us/visual-intro-to-machine-learning-part-1/)
1. [Deep Reinforcement Learning: Pong from Pixels](http://karpathy.github.io/2016/05/31/rl/)
1. [Inside Libratus, the Poker AI That Out-Bluffed the Best Humans](https://www.wired.com/2017/02/libratus/?imm_mid=0ed017&cmp=em-data-na-na-newsltr_ai_20170206)
1. [Machine Learning in Javascript: Introduction](http://burakkanber.com/blog/machine-learning-in-other-languages-introduction/)
1. [Realtime control of sequence generation with character based Long Short Term Memory Recurrent Neural Networks](http://www.iggi.org.uk/assets/IGGI-2016-Memo-A.pdf)
1. [Why is machine learning 'hard'?](http://ai.stanford.edu/~zayd/why-is-machine-learning-hard.html)
1. [A Return to Machine Learning](https://medium.com/@kcimc/a-return-to-machine-learning-2de3728558eb#.vlqnbo9yg) :rainbow: :bowtie:
1. [A Visual Introduction to Machine Learning](http://www.r2d3.us/visual-intro-to-machine-learning-part-1/) :rainbow: :bowtie:
1. [Machine Learning is Fun!](https://medium.com/@ageitgey/machine-learning-is-fun-80ea3ec3c471) :bowtie:
1. [Deep Reinforcement Learning: Pong from Pixels](http://karpathy.github.io/2016/05/31/rl/) :rainbow:
1. [Inside Libratus, the Poker AI That Out-Bluffed the Best Humans](https://www.wired.com/2017/02/libratus/? imm_mid=0ed017&cmp=em-data-na-na-newsltr_ai_20170206) :bowtie:
1. [Machine Learning in Javascript: Introduction](http://burakkanber.com/blog/machine-learning-in-other-languages-introduction/) :bowtie:
1. [Realtime control of sequence generation with character based Long Short Term Memory Recurrent Neural Networks](http://www.iggi.org.uk/assets/IGGI-2016-Memo-A.pdf) :sweat_smile:
1. [Why is machine learning 'hard'?](http://ai.stanford.edu/~zayd/why-is-machine-learning-hard.html) :bowtie:
1. [Unreasonable effectiveness of RNNs](http://karpathy.github.io/2015/05/21/rnn-effectiveness/) :sweat_smile:

## Courses
1. [The Neural Aesthetic @ SchoolOfMa, Summer 2016](http://ml4a.github.io/classes/neural-aesthetic/)
1. [The Neural Aesthetic @ SchoolOfMa, Summer 2016](http://ml4a.github.io/classes/neural-aesthetic/) :rainbow: :bowtie:

## Examples
1. [A Deep Q Reinforcement Learning Demo](http://projects.rajivshah.com/rldemo/)
1. [How to use Q Learning in Video Games Easily](https://github.com/llSourcell/q_learning_demo)
1. [K-nearest](https://twitter.com/MaximilianLloyd/status/814942799351185408)
1. [The Infinite Drum Machine](https://aiexperiments.withgoogle.com/drum-machine/view/)
1. [Visualizing the perceptron training algorithm](https://kwichmann.github.io/ml_sandbox/perceptron/)
1. [A Deep Q Reinforcement Learning Demo](http://projects.rajivshah.com/rldemo/) :bowtie:
1. [How to use Q Learning in Video Games Easily](https://github.com/llSourcell/q_learning_demo) :rainbow: :bowtie:
1. [K-nearest](https://twitter.com/MaximilianLloyd/status/814942799351185408) :bowtie:
1. [The Infinite Drum Machine](https://aiexperiments.withgoogle.com/drum-machine/view/) :rainbow: :bowtie:
1. [Visualizing the perceptron training algorithm](https://kwichmann.github.io/ml_sandbox/perceptron/) :rainbow: :bowtie:

## Projects
1. [Bidirectional LSTM for IMDB sentiment classification](https://transcranial.github.io/keras-js/#/imdb-bidirectional-lstm)
1. [Land Lines](https://medium.com/@zachlieberman/land-lines-e1f88c745847#.1157xmhw8)
1. [nnvis - Topological Visualisation of a Convolutional Neural Network](http://terencebroad.com/convnetvis/vis.html)
1. [Bidirectional LSTM for IMDB sentiment classification](https://transcranial.github.io/keras-js/#/imdb-bidirectional-lstm) :sweat_smile:
1. [Land Lines](https://medium.com/@zachlieberman/land-lines-e1f88c745847#.1157xmhw8)
1. [nnvis - Topological Visualisation of a Convolutional Neural Network](http://terencebroad.com/convnetvis/vis.html) :rainbow: :bowtie:
1. [char-rnn A character level language model (a fancy text generator)](https://github.com/karpathy/char-rnn) :rainbow: :sweat_smile:


## Videos
* Reinforcement Learning
1. [Artificial Intelligence in Google's Dinosaur (English Sub)](https://www.youtube.com/watch?v=P7XHzqZjXQs)
1. [How to use Q Learning in Video Games Easily](https://www.youtube.com/watch?v=A5eihauRQvo&feature=youtu.be)
1. [Artificial Intelligence in Google's Dinosaur (English Sub)](https://www.youtube.com/watch?v=P7XHzqZjXQs) :bowtie:
1. [How to use Q Learning in Video Games Easily](https://www.youtube.com/watch?v=A5eihauRQvo&feature=youtu.be) :bowtie:
* Evolutionary Algorithms
1. [Evolving Swimming Soft-Bodied Creatures](https://www.youtube.com/watch?v=4ZqdvYrZ3ro)
1. [Harnessing evolutionary creativity: evolving soft-bodied animats in simulated physical environments](https://www.youtube.com/watch?v=CXTZHHQ7ZiQ&feature=youtu.be)
1. [Reproduce image with genetic algorithm](https://www.youtube.com/watch?v=iV-hah6xs2A)
1. [Evolving Swimming Soft-Bodied Creatures](https://www.youtube.com/watch?v=4ZqdvYrZ3ro) :rainbow: :bowtie:
1. [Harnessing evolutionary creativity: evolving soft-bodied animats in simulated physical environments](https://www.youtube.com/watch?v=CXTZHHQ7ZiQ&feature=youtu.be) :rainbow: :bowtie:
1. [Reproduce image with genetic algorithm](https://www.youtube.com/watch?v=iV-hah6xs2A) :bowtie:

## Tools
1. [ConvNetJS - Javascript library for training Deep Learning models (Neural Networks) ](http://cs.stanford.edu/people/karpathy/convnetjs/)
1. [RecurrentJS - Deep Recurrent Neural Networks and LSTMs in Javascript](https://github.com/shiffman/recurrentjs)
1. [WORD2VEC](http://technobium.com/find-words-similarity-using-deeplearning4j-word2vec/)
1. [ConvNetJS - Javascript library for training Deep Learning models (Neural Networks) ](http://cs.stanford.edu/people/karpathy/convnetjs/) :sweat_smile:
1. [RecurrentJS - Deep Recurrent Neural Networks and LSTMs in Javascript](https://github.com/shiffman/recurrentjs) :sweat_smile:
1. [WORD2VEC](http://technobium.com/find-words-similarity-using-deeplearning4j-word2vec/) :sweat_smile:

### TensorFlow
1. [Projector](http://projector.tensorflow.org/)
1. [Magenta](https://github.com/tensorflow/magenta)
1. [Projector](http://projector.tensorflow.org/) :sweat_smile:
1. [Magenta](https://github.com/tensorflow/magenta) :rainbow:

### Tensorflow posts
1. [Big deep learning news: Google Tensorflow chooses Keras](http://www.fast.ai/2017/01/03/keras/)
1. [Simple end-to-end TensorFlow examples](http://bcomposes.com/2015/11/26/simple-end-to-end-tensorflow-examples/)

### t-SNE
1. [t-SNE](https://lvdmaaten.github.io/tsne/)
1. [t-SNE](https://scienceai.github.io/tsne-js/)
1. [t-SNE](https://lvdmaaten.github.io/tsne/) :sweat_smile:
1. [t-SNE](https://scienceai.github.io/tsne-js/) :sweat_smile:
1. [An illustrated introduction to the t-SNE algorithm](https://www.oreilly.com/learning/an-illustrated-introduction-to-the-t-sne-algorithm)
1. [Visualizing Data Using t-SNE](https://www.youtube.com/watch?v=RJVL80Gg3lA&list=UUtXKDgv1AVoG88PLl8nGXmw)
1. [Visualizing Data Using t-SNE](https://www.youtube.com/watch?v=RJVL80Gg3lA&list=UUtXKDgv1AVoG88PLl8nGXmw) :rainbow: