机器学习

博客

• Flaire of Machine Learning
  

  • Understanding the backward pass through Batch Normalization Layer

• https://r2rt.com/
  

  • Recurrent Neural Networks in Tensorflow I
  • Written Memories: Understanding, Deriving and Extending the LSTM
    

• http://practicalcryptography.com/miscellaneous/
  

  • Mel Frequency Cepstral Coefficient (MFCC) tutorial
  • An Intuitive Discrete Fourier Transform Tutorial
  • Speech Enhancement tutorial: Spectral Subraction
  • Voice Activity Detection (VAD) Tutorial

• Josh Meyer's Website
  

  • How to use an Existing DNN Recognizer for Decoding in Kaldi
  • How to Train a Deep Neural Net Acoustic Model with Kaldi
  • How to use an Existing GMM Recognizer for Decoding in Kaldi
  • Getting started with the Merlin Speech Synthesis Toolkit

• John Glover
  

  • 2016-08-25: An introduction to Generative Adversarial Networks.
  • 2015-12-16: Generating sound with recurrent neural networks.

• Sam's Research Blog
  

• Andrew L. Beam
  

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  • YOU CAN PROBABLY USE DEEP LEARNING EVEN IF YOUR DATA ISN'T THAT BIG

• Edwin Chen
  

  • Exploring LSTMs

• http://rbharath.github.io/
  

  • A Short Overview of Drug Discovery

• ml4a
  

  • Pix2Pix

• http://nlp.yvespeirsman.be/blog/
  

  • Anything2Vec, or How Word2Vec Conquered NLP

• TheSpectator
  

  • Cognitive Machine Learning (1):Learning to Explain
  • Cognitive Machine Learning(2): Uncertain Thoughts

• http://iamtrask.github.io/
  

  • Anyone Can Learn To Code an LSTM-RNN in Python (Part 1: RNN)
    

• https://blog.acolyer.org/
  

  • Neural Turing machines
  • Memory networks
  • Recurrent Neural Networkmodels

• http://karpathy.github.io/
  

• The Unreasonable Effectiveness of Recurrent Neural Networks

• Deep Reinforcement Learning: Pong from Pixels

• http://colah.github.io/
  

• Attention and Augmented Recurrent Neural Networks

• Understanding LSTM Networks

• http://www.wildml.com/
  

  • UNDERSTANDING CONVOLUTIONAL NEURAL NETWORKS FOR NLP
  • ATTENTION AND MEMORY IN DEEP LEARNING AND NLP
  • RECURRENT NEURAL NETWORKS TUTORIAL
  • RNNs in Tensorflow, a Practical Guide and Undocumented Features

• http://mccormickml.com/
  

  • Word2Vec Tutorial - The Skip-Gram Model

• Concept Search on Wikipedia

• http://nlpforhackers.io/
  

  • Complete guide to build your own Named Entity Recognizer with Python
  • Training a NER System Using a Large Dataset

• http://www.offconvex.org/
  

• https://blog.openai.com/
  

  • Evolution Strategies as a Scalable Alternative to Reinforcement Learning
  • Learning to Communicate
  • Generative Models

• http://www.inference.vc/
  

  • Evolution Strategies, Variational Optimisation and Natural ES

• fast.ai
  

  • 6—BUILDING RNNS
  • Alternatives to a Degree to Prove Yourself in Deep Learning

• Practical Business Python
  

  • Overview of Python Visualization Tools

Media

• https://www.oreilly.com/topics/ai
  
• http://waitbutwhy.com/
  
  • The Elon Musk Post Series

在线电子书

• http://web.stanford.edu/~jurafsky/slp3/
  
  语音和语言处理 3rd
• http://www.nltk.org/book/
  
  NLTK python3

数学物理

• COUNT BAYESIE
  
  • Kullback-Leibler Divergence Explained
• Animated math
  
  Animated math

• https://degiuli.com/
  
  • MONTE CARLO METHODS, WHERE MATH AND CHANCE MEET
• https://www.quantamagazine.org/
  
  • Quanta Science Podcast
  • The Quantum Fabric of Space-Time
• https://bitworking.org/news/
  
• https://betterexplained.com/archives/
  
• http://www.myphysicslab.com/
  

工具

• Markdown
  Markdown Cheatsheet
  Remarkable

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