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Title: GitHub - CodingTrain/Machine-Learning: Examples and experiments around ML for upcoming Coding Train videos

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Description: Examples and experiments around ML for upcoming Coding Train videos - CodingTrain/Machine-Learning

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https://github.com/CodingTrain/Machine-Learning#articles--posts
A Return to Machine Learninghttps://medium.com/@kcimc/a-return-to-machine-learning-2de3728558eb#.vlqnbo9yg
A Visual Introduction to Machine Learninghttp://www.r2d3.us/visual-intro-to-machine-learning-part-1/
Machine Learning is Fun!https://medium.com/@ageitgey/machine-learning-is-fun-80ea3ec3c471
Deep Reinforcement Learning: Pong from Pixelshttp://karpathy.github.io/2016/05/31/rl/
Inside Libratus, the Poker AI That Out-Bluffed the Best Humanshttps://www.wired.com/2017/02/libratus/?imm_mid=0ed017&cmp=em-data-na-na-newsltr_ai_20170206
Machine Learning in Javascript: Introductionhttp://burakkanber.com/blog/machine-learning-in-other-languages-introduction/
Realtime control of sequence generation with character based Long Short Term Memory Recurrent Neural Networkshttp://www.iggi.org.uk/assets/IGGI-2016-Memo-A.pdf
Why is machine learning 'hard'?http://ai.stanford.edu/~zayd/why-is-machine-learning-hard.html
Unreasonable effectiveness of RNNshttp://karpathy.github.io/2015/05/21/rnn-effectiveness/
colah's bloghttp://colah.github.io/
Machine Learning Website with many Tutorial of Machine Learning‪https://machinelearningmastery.com/start-here/%E2%80%AC
Beginners tutorial for decision tree implementationhttps://www.dezyre.com/data-science-in-r-programming-tutorial/decision-tree-tutorial
Machine Learning Beginner tutorial Supervised and Unsupervised Learninghttp://dataaspirant.com/2014/09/19/supervised-and-unsupervised-learning/%E2%80%AC
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Distill - Demystifying Machine Learning Researchhttp://distill.pub/
Machine Learning in Javascripthttp://burakkanber.com/tag/ml-in-js/
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Rohan & Lenny #3: Recurrent Neural Networks & LSTMshttps://ayearofai.com/rohan-lenny-3-recurrent-neural-networks-10300100899b
Backpropogating an LSTM: A Numerical Examplehttps://medium.com/@aidangomez/let-s-do-this-f9b699de31d9
Naive Bayes for Dummies; A Simple Explanationhttp://blog.aylien.com/naive-bayes-for-dummies-a-simple-explanation/
Machine Learning Crash Course @ Berkeleyhttps://ml.berkeley.edu/blog/tutorials/
How to approach almost any ML problem?http://blog.kaggle.com/2016/07/21/approaching-almost-any-machine-learning-problem-abhishek-thakur/
Technical Notes on ML & AI by Chris Albonhttps://chrisalbon.com/#machine_learning
Naive Bayes and Text Classificationhttps://sebastianraschka.com/Articles/2014_naive_bayes_1.html
First Contact With TensorFlowhttps://torres.ai/research-teaching/tensorflow/first-contact-with-tensorflow-book/first-contact-with-tensorflow/
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A first encounter with machine learninghttps://www.ics.uci.edu/~welling/teaching/ICS273Afall11/IntroMLBook.pdf
Natural Language Processing with Pythonhttps://www.nltk.org/book/
A Brief Introduction to Neural Networkshttp://www.dkriesel.com/en/science/neural_networks
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The Infinite Drum Machinehttps://aiexperiments.withgoogle.com/drum-machine/view/
Visualizing various ML algorithmshttps://kwichmann.github.io/ml_sandbox/
Image-to-Image - from lines to catshttp://affinelayer.com/pixsrv/
Recurrent Neural Network Tutorial for Artistshttp://blog.otoro.net/2017/01/01/recurrent-neural-network-artist/
Browser Self-Driving Carhttp://janhuenermann.com/projects/learning-to-drive
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The Neural Network Zoo (cheat sheet of nn architectures)http://www.asimovinstitute.org/neural-network-zoo/
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https://github.com/CodingTrain/Machine-Learning#projects
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Land Lineshttps://medium.com/@zachlieberman/land-lines-e1f88c745847#.1157xmhw8
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char-rnn A character level language model (a fancy text generator)https://github.com/karpathy/char-rnn
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Artificial Intelligence in Google's Dinosaur (English Sub)https://www.youtube.com/watch?v=P7XHzqZjXQs
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Evolving Swimming Soft-Bodied Creatureshttps://www.youtube.com/watch?v=4ZqdvYrZ3ro
Harnessing evolutionary creativity: evolving soft-bodied animats in simulated physical environmentshttps://www.youtube.com/watch?v=CXTZHHQ7ZiQ&feature=youtu.be
Reproduce image with genetic algorithmhttps://www.youtube.com/watch?v=iV-hah6xs2A
Video Lectures of Deep Learning‪http://videolectures.net/deeplearning2015_montreal/
Neural networks class - Université de Sherbrookehttps://www.youtube.com/playlist?list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH
A Friendly Introduction to Machine Learning‪https://www.youtube.com/watch?v=IpGxLWOIZy4
A friendly introduction to Deep Learning and Neural Networkshttps://www.youtube.com/watch?v=BR9h47Jtqyw&t=837s
A friendly introduction to Convolutional Neural Networks and Image Recognitionhttps://www.youtube.com/watch?v=2-Ol7ZB0MmU
Deep Learning Demystifiedhttps://www.youtube.com/watch?v=Q9Z20HCPnww&t=225s&list=PLVZqlMpoM6kbaeySxhdtgQPFEC5nV7Faa&index=4
How Deep Neural Networks Workhttps://www.youtube.com/watch?v=ILsA4nyG7I0&t=1269s&list=PLVZqlMpoM6kbaeySxhdtgQPFEC5nV7Faa&index=1
How Convolutional Neural Networks workhttps://www.youtube.com/watch?v=FmpDIaiMIeA&t=700s&list=PLVZqlMpoM6kbaeySxhdtgQPFEC5nV7Faa&index=2
MIT 6.034 Artificial Intelligence, Fall 2010https://www.youtube.com/playlist?list=PLUl4u3cNGP63gFHB6xb-kVBiQHYe_4hSi
https://github.com/CodingTrain/Machine-Learning#resources
Awesome Machine Learninghttps://github.com/josephmisiti/awesome-machine-learning
QA StackOverflow Machine Learning Algorithmshttp://stackoverflow.com/questions/20898300/whats-the-other-major-approach-paradigms-in-machine-learning-besides-baysian-me
‪Free dataset for projectshttps://www.dataquest.io/blog/free-datasets-for-projects
Facial Recognition Databasehttps://www.kairos.com/blog/166-60-facial-recognition-databases
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 thingshttps://itunes.apple.com/app/id1055459116
Machine Learning Resourceshttp://blog.yhat.com/posts/ML-resources-you-should-know.html
Isochrones using the Google Maps Distance Matrix APIhttp://blog.yhat.com/posts/isochrones-isocronut.html
Index of Best AI/Machine Learning Resourceshttps://hackernoon.com/index-of-best-ai-machine-learning-resources-71ba0c73e34d#.f0vx1erj9
https://github.com/CodingTrain/Machine-Learning#newsletter
Data Sciencehttps://www.datascienceweekly.org/
Data Elixirhttps://dataelixir.com/
Artificial Intelligence Weeklyhttp://aiweekly.co/
Data Aspiranthttp://dataaspirant.com/
https://github.com/CodingTrain/Machine-Learning#tools
ConvNetJS - Javascript library for training Deep Learning models (Neural Networks) http://cs.stanford.edu/people/karpathy/convnetjs/
RecurrentJS - Deep Recurrent Neural Networks and LSTMs in Javascripthttps://github.com/shiffman/recurrentjs
AIXIjs - JavaScript demo for running General Reinforcement Learning (RL) agentshttps://github.com/aslanides/aixijs/
WORD2VEChttp://technobium.com/find-words-similarity-using-deeplearning4j-word2vec/
Neuro.jshttps://github.com/janhuenermann/neurojs
‪Google Chrome Extensión to download all Image of the Google Searchhttps://chrome.google.com/webstore/detail/fatkun-batch-download-ima/nnjjahlikiabnchcpehcpkdeckfgnohf?hl=es%E2%80%AC
Scikit-Learnhttp://scikit-learn.org/
https://github.com/CodingTrain/Machine-Learning#tensorflow
Projectorhttp://projector.tensorflow.org/
Magentahttps://github.com/tensorflow/magenta
TensorFlow and Flaskhttps://blog.metaflow.fr/tensorflow-how-to-freeze-a-model-and-serve-it-with-a-python-api-d4f3596b3adc#.96tvigb98_
basic pipeline, minus TensorFlow plus a very basic placeholder functionhttp://www.patrickhebron.com/learning-machines/week8.html
Awesome Tensorflow - curated list of TensorFlow tutorialshttps://github.com/jtoy/awesome-tensorflow
https://github.com/CodingTrain/Machine-Learning#tensorflow-posts
Big deep learning news: Google Tensorflow chooses Kerashttp://www.fast.ai/2017/01/03/keras/
Simple end-to-end TensorFlow exampleshttp://bcomposes.com/2015/11/26/simple-end-to-end-tensorflow-examples/
TensorFlow website Getting Startedhttps://www.tensorflow.org/get_started/get_started
https://github.com/CodingTrain/Machine-Learning#t-sne
t-SNEhttps://lvdmaaten.github.io/tsne/
t-SNEhttps://scienceai.github.io/tsne-js/
An illustrated introduction to the t-SNE algorithmhttps://www.oreilly.com/learning/an-illustrated-introduction-to-the-t-sne-algorithm
Visualizing Data Using t-SNEhttps://www.youtube.com/watch?v=RJVL80Gg3lA&list=UUtXKDgv1AVoG88PLl8nGXmw
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URLs of crawlers that visited me.