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
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
Have Fun With Machine Learning
Interview Resources
41 Essential Machine Learning Interview Questions (with answers)
How can a computer science graduate student prepare himself for data scientist interviews?
What are the key skills of a data scientist?
Artificial Intelligence
MIT 6.034 Artificial Intelligence Lecture Videos, Complete Course

Genetic Algorithms
Simple Implementation of Genetic Algorithms in Python (Part 1), Part 2
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
Machine Learning FAQs on Quora
Kaggle Competitions WriteUp
How to Rank 10% in Your First Kaggle Competition
Cheat Sheets

Classification
What are the advantages of different classification algorithms?
Simple guide to confusion matrix terminology
Linear Regression

 Assumptions of Linear Regression, Stack Exchange
 Linear Regression Comprehensive Resource
 Applying and Interpreting Linear Regression
 What does having constant variance in a linear regression model mean?
 Difference between linear regression on y with x and x with y
 Is linear regression valid when the dependant variable is not normally distributed?
Multicollinearity and VIF
Difference between logit and probit models, Logistic Regression Wiki, Probit Model Wiki
Pseudo R2 for Logistic Regression, How to calculate, Other Details
Guide to an indepth understanding of logistic regression
Model Validation using Resampling
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
 Torch vs. Theano
 dl4j vs. torch7 vs. theano
 Deep Learning Libraries by Language
 Theano)
 Website
 Theano Introduction
 Theano Tutorial
 Good Theano Tutorial
 Logistic Regression using Theano for classifying digits
 MLP using Theano
 CNN using Theano
 RNNs using Theano
 LSTM for Sentiment Analysis in Theano
 RBM using Theano
 DBNs using Theano
 All Codes
 Deep Learning Implementation Tutorials  Keras and Lasagne
 Torch
 Caffe
 TensorFlow
Feed Forward Networks
 A Quick Introduction to Neural Networks
 Implementing a Neural Network from scratch, Code
 Speeding up your Neural Network with Theano and the gpu, Code
 Basic ANN Theory
 Role of Bias in Neural Networks
 Choosing number of hidden layers and nodes,2,3
 Backpropagation in Matrix Form
 ANN implemented in C++  AI Junkie
 Simple Implementation
 NN for Beginners
 Regression and Classification with NNs (Slides)
 Another Intro
Recurrent and LSTM Networks
 awesomernn: list of resources (GitHub Repo)
 Recurrent Neural Net Tutorial Part 1, Part 2, Part 3, Code
 NLP RNN Representations
 The Unreasonable effectiveness of RNNs, Torch Code, Python Code
 Intro to RNN, LSTM
 An application of RNN
 Optimizing RNN Performance
 Simple RNN
 AutoGenerating Clickbait with RNN
 Sequence Learning using RNN (Slides)
 Machine Translation using RNN (Paper)
 Music generation using RNNs (Keras)
 Using RNN to create onthefly dialogue (Keras)
 Long Short Term Memory (LSTM)
 Understanding LSTM Networks
 LSTM explained
 Beginner’s Guide to LSTM
 Implementing LSTM from scratch, Python/Theano code
 Torch Code for characterlevel language models using LSTM
 LSTM for Kaggle EEG Detection competition (Torch Code)
 LSTM for Sentiment Analysis in Theano
 Deep Learning for Visual Q&A  LSTM  CNN, Code
 Computer Responds to email using LSTM  Google
 LSTM dramatically improves Google Voice Search, Another Article
 Understanding Natural Language with LSTM Using Torch
 Torch code for Visual Question Answering using a CNN+LSTM model
 Gated Recurrent Units (GRU)
Restricted Boltzmann Machine
Autoencoders: Unsupervised (applies BackProp after setting target = input)
Convolutional Neural Networks
A curated list of speech and natural language processing resources
Understanding Natural Language with Deep Neural Networks Using Torch

 LDA, LSA, Probabilistic LSA
 What is a good explanation of Latent Dirichlet Allocation?
 Awesome LDA Explanation!. Another good explanation
 The LDA Buffet Intuitive Explanation
 Difference between LSI and LDA
 Original LDA Paper
 alpha and beta in LDA
 Intuitive explanation of the Dirichlet distribution
 Topic modeling made just simple enough
 Online LDA, Online LDA with Spark
 LDA in Scala, Part 2
 Segmentation of Twitter Timelines via Topic Modeling
 Topic Modeling of Twitter Followers
word2vec
 Google word2vec
 Bag of Words Model Wiki
 word2vec Tutorial
 A closer look at Skip Gram Modeling
 Skip Gram Model Tutorial, CBoW Model
 Word Vectors Kaggle Tutorial Python, Part 2
 Making sense of word2vec
 word2vec explained on deeplearning4j
 Quora word2vec
 Other Quora Resources, 2, 3
 word2vec, DBN, RNTN for Sentiment Analysis
Text Clustering
Text Classification
Kaggle Tutorial Bag of Words and Word vectors, Part 2, Part 3
A closer look at Skip Gram Modeling
Computer Vision

Support Vector Machine
Comparisons
Software
Kernels
Probabilities post SVM

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
Evaluating Random Forests for Survival Analysis Using Prediction Error Curve
Why doesn’t Random Forest handle missing values in predictors?
Some Questions for R implementation, 2, 3
Boosting
Gradient Boosting Machine
xgboost
AdaBoost
Ensembling models with R, Ensembling Regression Models in R, Intro to Ensembles in R
How are classifications merged in an ensemble classifier?
Stacking Models

Vapnik–Chervonenkis Dimension
Do ensemble techniques increase VCdimension?
Bayesian Machine Learning

Semi Supervised Learning

Optimization
Mean Variance Portfolio Optimization with R and Quadratic Programming
The Interplay of Optimization and Machine Learning Research
Other Tutorials
For a collection of Data Science Tutorials using R, please refer to this list.
For a collection of Data Science Tutorials using Python, please refer to this list.