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Expectation-Maximization (EM)
 

 


A Beginner’s Guide to Restricted Boltzmann Machines  
An overview of convolutional neural network architectures (CNNs)  
An overview of gradient descent optimization algorithms  Sebastian Ruder
Awesome deep vision   - curated list of deep learning resources for computer vision.
Awesome TensorFlow   - a curated list of TensorFlow projects
Deep learning reading list  
Deep Learning Tutorials — Deep Learning v0.1 documentation  
GIBBS SAMPLING FOR THE UNINITIATED  Philip Resnik, Eric Hardisty
MLDemos  Basilio Noris - Visualization of machine learning.
Most Cited Deep Learning Papers  Terry Taewoong Um
Notebooks and code for the book "Introduction to Machine Learning with Python"  
Probabilistic Programming for Anomaly Detection  
scikit-learn tutorials from Kaggle  
State of the art Stochastic Gradient Descent methods: an excellent overview  Yaroslav Bulatov
Top 10 algorithms in data mining  Xindong Wu, Vipin Kumar, J Ross Quinlan, Joydeep Ghosh, Qiang Yang, Hiroshi Motoda, Geoffrey J McLachlan, Angus Ng, Bing Liu, S Yu Philip, Zhi-Hua Zhou, Michael Steinbach, David J Hand, Dan Steinberg
Training Sequence Models with Attention  Awni Hannun - practical tips to train seq-to-seq models.
Visualization of neural network learning  
What it takes to build great machine learning products  Aria Haghighi