Machine Learning & Deep Learning Tutorials

This repository contains a topicwise curated list of Machine Learning and Deep Learning tutorials, articles and other resources. Other awesome lists can be found in this list.

If you want to contribute to this list, please read Contributing Guidelines.

Curated list of R tutorials for Data Science, NLP and Machine Learning.

Curated list of Python tutorials for Data Science, NLP and Machine Learning.
Contents
 Miscellaneous
 Interview Resources
 Artificial Intelligence
 Genetic Algorithms
 Statistics
 Useful Blogs
 Resources on Quora
 Resources on Kaggle
 Cheat Sheets
 Classification
 Linear Regression
 Logistic Regression
 Model Validation using Resampling
 Deep Learning
 Natural Language Processing
 Computer Vision
 Support Vector Machine
 Reinforcement Learning
 Decision Trees
 Random Forest / Bagging
 Boosting
 Ensembles
 Stacking Models
 VC Dimension
 Bayesian Machine Learning
 Semi Supervised Learning
 Optimizations
 Other Useful Tutorials
Miscellaneous

A curated list of awesome Machine Learning frameworks, libraries and software

A curated list of awesome data visualization libraries and resources.

An awesome Data Science repository to learn and apply for real world problems

Machine Learning algorithms that you should always have a strong understanding of

Difference between Linearly Independent, Orthogonal, and Uncorrelated Variables

Indepth introduction to machine learning in 15 hours of expert videos
Interview Resources

41 Essential Machine Learning Interview Questions (with answers)

How can a computer science graduate student prepare himself for data scientist interviews?
Artificial Intelligence
Genetic Algorithms
Statistics

Stat Trek Website  A dedicated website to teach yourselves Statistics

Learn Statistics Using Python  Learn Statistics using an applicationcentric programming approach

Statistics for Hackers  Slides  @jakevdp  Slides by Jake VanderPlas

Online Statistics Book  An Interactive Multimedia Course for Studying Statistics

Tutorials

OpenIntro Statistics  Free PDF textbook
Useful Blogs

Edwin Chen's Blog  A blog about Math, stats, ML, crowdsourcing, data science

The Data School Blog  Data science for beginners!

ML Wave  A blog for Learning Machine Learning

Andrej Karpathy  A blog about Deep Learning and Data Science in general

Colah's Blog  Awesome Neural Networks Blog

Alex Minnaar's Blog  A blog about Machine Learning and Software Engineering

Statistically Significant  Andrew Landgraf's Data Science Blog

Simply Statistics  A blog by three biostatistics professors

Yanir Seroussi's Blog  A blog about Data Science and beyond

fastML  Machine learning made easy

Trevor Stephens Blog  Trevor Stephens Personal Page

no free hunch  kaggle  The Kaggle Blog about all things Data Science

A Quantitative Journey  outlace  learning quantitative applications

r4stats  analyze the world of data science, and to help people learn to use R

Variance Explained  David Robinson's Blog

AI Junkie  a blog about Artificial Intellingence

Deep Learning Blog by Tim Dettmers Making deep learning accessible

J Alammar's Blog Blog posts about Machine Learning and Neural Nets

Adam Geitgey  Easiest Introduction to machine learning
Resources on Quora
Kaggle Competitions WriteUp
Cheat Sheets
Classification
Linear Regression

Multicollinearity and VIF
Logistic Regression

Difference between logit and probit models, Logistic Regression Wiki, Probit Model Wiki

Pseudo R2 for Logistic Regression, How to calculate, Other Details
Model Validation using Resampling


Overfitting and Cross Validation
Deep Learning

A curated list of awesome Deep Learning tutorials, projects and communities

Interesting Deep Learning and NLP Projects (Stanford), Website

Understanding Natural Language with Deep Neural Networks Using Torch

Introduction to Deep Learning Using Python (GitHub), Good Introduction Slides

Video Lectures Oxford 2015, Video Lectures Summer School Montreal

Neural Machine Translation

Deep Learning Frameworks


Caffe

TensorFlow

Feed Forward Networks
 Recurrent and LSTM Networks

The Unreasonable effectiveness of RNNs, Torch Code, Python Code

Long Short Term Memory (LSTM)

Gated Recurrent Units (GRU)

Restricted Boltzmann Machine

Autoencoders: Unsupervised (applies BackProp after setting target = input)

Convolutional Neural Networks
Natural Language Processing

A curated list of speech and natural language processing resources

Understanding Natural Language with Deep Neural Networks Using Torch

word2vec

Text Clustering

Text Classification

Kaggle Tutorial Bag of Words and Word vectors, Part 2, Part 3
Computer Vision
Support Vector Machine

Comparisons

Software

Kernels

Probabilities post SVM
Reinforcement Learning
Decision Trees

What is entropy and information gain in the context of building decision trees?

How do decision tree learning algorithms deal with missing values?

Comparison of Different Algorithms

CART

CTREE

CHAID

MARS

Probabilistic Decision Trees
Random Forest / Bagging

Evaluating Random Forests for Survival Analysis Using Prediction Error Curve

Why doesn't Random Forest handle missing values in predictors?
Boosting

Gradient Boosting Machine

xgboost

AdaBoost