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Awesome Machine Learning Tutorials – Massive Collection of Resources
Machine Learning & Deep Learning Tutorials
 This repository contains a topicwise curated list of Machine Learning and Deep Learning tutorials, articles and other resources.
Contents
 Introduction
 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
Introduction
Machine Learning Course by Andrew Ng (Stanford University) Curated List of Machine Learning Resources
 Indepth introduction to machine learning in 15 hours of expert videos
 An Introduction to Statistical Learning
 List of Machine Learning University Courses
 Machine Learning for Software Engineers
 Dive into Machine Learning
 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
 The Open Source Data Science Masters
 Machine Learning FAQs on Cross Validated
 Machine Learning algorithms that you should always have a strong understanding of
 Difference between Linearly Independent, Orthogonal, and Uncorrelated Variables
 List of Machine Learning Concepts
 Slides on Several Machine Learning Topics
 MIT Machine Learning Lecture Slides
 Comparison Supervised Learning Algorithms
 Learning Data Science Fundamentals
 Machine Learning mistakes to avoid
 Statistical Machine Learning Course
 TheAnalyticsEdge edX Notes and Codes
 Have Fun With Machine Learning
 Twitter’s Most Shared #machineLearning Content From The Past 7 Days
Interview Resources
41 Essential Machine Learning Interview Questions (with answers) How can a computer science graduate student prepare himself for data scientist interviews?
 How do I learn Machine Learning?
 FAQs about Data Science Interviews
 What are the key skills of a data scientist?
 The Big List of DS/ML Interview Resources
Artificial Intelligence
Awesome Artificial Intelligence (GitHub Repo) UC Berkeley CS188 Intro to AI, Lecture Videos, 2
 Programming Community Curated Resources for learning Artificial Intelligence
 MIT 6.034 Artificial Intelligence Lecture Videos, Complete Course
 edX course  Klein & Abbeel
 Udacity Course  Norvig & Thrun
 TED talks on AI
Genetic Algorithms
Genetic Algorithms Wikipedia Page Simple Implementation of Genetic Algorithms in Python (Part 1), Part 2
 Genetic Algorithms vs Artificial Neural Networks
 Genetic Algorithms Explained in Plain English
 Genetic Programming
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
 What is a Sampling Distribution?
 Tutorials
 What is an Unbiased Estimator?
 Goodness of Fit Explained
 What are QQ Plots?
 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
 Ethen’s Notebook Collection – Continuously updated machine learning documentations (mainly in Python3). Contents include educational implementation of machine learning algorithms from scratch and opensource library usage
Resources on Quora
Most Viewed Machine Learning writers Data Science Topic on Quora
 William Chen’s Answers
 Michael Hochster’s Answers
 Ricardo Vladimiro’s Answers
 Storytelling with Statistics
 Data Science FAQs on Quora
 Machine Learning FAQs on Quora
Kaggle Competitions WriteUp
How to almost win Kaggle Competitions Convolution Neural Networks for EEG detection
 Facebook Recruiting III Explained
 Predicting CTR with Online ML
 How to Rank 10% in Your First Kaggle Competition
Cheat Sheets
Classification
Does Balancing Classes Improve Classifier Performance? What is Deviance?
 When to choose which machine learning classifier?
 What are the advantages of different classification algorithms?
 ROC and AUC Explained (related video)
 An introduction to ROC analysis
 Simple guide to confusion matrix terminology
Linear Regression
General 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
 Residual Analysis
 Outliers
 Elastic Net
Logistic Regression
Logistic Regression Wiki Geometric Intuition of Logistic Regression
 Obtaining predicted categories (choosing threshold)
 Residuals in logistic regression
 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
 Cross Validation
Deep Learning
fast.ai – Practical Deep Learning For Coders fast.ai – Cutting Edge Deep Learning For Coders
 A curated list of awesome Deep Learning tutorials, projects and communities
 Deep Learning Papers Reading Roadmap
 Lots of Deep Learning Resources
 Interesting Deep Learning and NLP Projects (Stanford), Website
 Core Concepts of Deep Learning
 Understanding Natural Language with Deep Neural Networks Using Torch
 Stanford Deep Learning Tutorial
 Deep Learning FAQs on Quora
 Google+ Deep Learning Page
 Recent Reddit AMAs related to Deep Learning, Another AMA
 Where to Learn Deep Learning?
 Deep Learning nvidia concepts
 Introduction to Deep Learning Using Python (GitHub), Good Introduction Slides
 Video Lectures Oxford 2015, Video Lectures Summer School Montreal
 Deep Learning Software List
 Hacker’s guide to Neural Nets
 Top arxiv Deep Learning Papers explained
 Geoff Hinton Youtube Vidoes on Deep Learning
 Awesome Deep Learning Reading List
 Deep Learning Comprehensive Website, Software
 deeplearning Tutorials
 AWESOME! Deep Learning Tutorial
 Deep Learning Basics
 Intuition Behind Backpropagation
 Stanford Tutorials
 Train, Validation & Test in Artificial Neural Networks
 Artificial Neural Networks Tutorials
 Neural Networks FAQs on Stack Overflow
 Deep Learning Tutorials on deeplearning.net
 Neural Networks and Deep Learning Online Book
 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
 Website
 TensorFlow Examples for Beginners
 Stanford Tensorflow for Deep Learning Research Course
 Simplified Scikitlearn Style Interface to TensorFlow
 Learning TensorFlow GitHub Repo
 Benchmark TensorFlow GitHub
 Awesome TensorFlow List
 TensorFlow Book
 Android TensorFlow Machine Learning Example
 Creating Custom Model For Android Using 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
 LSTM for Human Activity Recognition
 Gated Recurrent Units (GRU)
 Time series forecasting with SequencetoSequence (seq2seq) rnn models
 Restricted Boltzmann Machine
 Autoencoders: Unsupervised (applies BackProp after setting target = input)
 Convolutional Neural Networks
An Intuitive Explanation of Convolutional Neural Networks Awesome Deep Vision: List of Resources (GitHub)
 Intro to CNNs
 Understanding CNN for NLP
 Stanford Notes, Codes, GitHub
 JavaScript Library (Browser Based) for CNNs
 Using CNNs to detect facial keypoints
 Deep learning to classify business photos at Yelp
 Interview with Yann LeCun  Kaggle
 Visualising and Understanding CNNs
 Network Representation Learning
Natural Language Processing
A curated list of speech and natural language processing resources Understanding Natural Language with Deep Neural Networks Using Torch
 tfidf explained
 Interesting Deep Learning NLP Projects Stanford, Website
 The Stanford NLP Group
 NLP from Scratch  Google Paper
 Graph Based Semi Supervised Learning for NLP
 Bag of Words
 Topic Modeling
Topic Modeling Wikipedia Probabilistic Topic Models Princeton PDF
 LDA Wikipedia, LSA Wikipedia, Probabilistic LSA Wikipedia
 What is a good explanation of Latent Dirichlet Allocation (LDA)?
 Introduction to LDA, Another good explanation
 The LDA Buffet – Intuitive Explanation
 Your Guide to Latent Dirichlet Allocation (LDA)
 Difference between LSI and LDA
 Original LDA Paper
 alpha and beta in LDA
 Intuitive explanation of the Dirichlet distribution
 topicmodels: An R Package for Fitting Topic Models
 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
 Multilingual Latent Dirichlet Allocation (LDA). (Tutorial here)
 Deep Belief Nets for Topic Modeling
 Gaussian LDA for Topic Models with Word Embeddings
 Python
 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
 Named Entity Recognitation
 Language learning with NLP and reinforcement learning
 Kaggle Tutorial Bag of Words and Word vectors, Part 2, Part 3
 What would Shakespeare say (NLP Tutorial)
 A closer look at Skip Gram Modeling
Computer Vision
Support Vector Machine
Highest Voted Questions about SVMs on Cross Validated Help me Understand SVMs!
 SVM in Layman’s terms
 How does SVM Work  Comparisons
 A tutorial on SVMs
 Practical Guide to SVC, Slides
 Introductory Overview of SVMs
 Comparisons
 Optimization Algorithms in Support Vector Machines
 Variable Importance from SVM
 Software
 Kernels
 Probabilities post SVM
Reinforcement Learning
Decision Trees
Wikipedia Page – Lots of Good Info FAQs about Decision Trees
 Brief Tour of Trees and Forests
 Tree Based Models in R
 How Decision Trees work?
 Weak side of Decision Trees
 Thorough Explanation and different algorithms
 What is entropy and information gain in the context of building decision trees?
 Slides Related to Decision Trees
 How do decision tree learning algorithms deal with missing values?
 Using Surrogates to Improve Datasets with Missing Values
 Good Article
 Are decision trees almost always binary trees?
 Pruning Decision Trees, Grafting of Decision Trees
 What is Deviance in context of Decision Trees?
 Discover structure behind data with decision trees – Grow and plot a decision tree to automatically figure out hidden rules in your data
 Comparison of Different Algorithms
 CART
 CTREE
 CHAID
 MARS
 Probabilistic Decision Trees
Random Forest / Bagging
Awesome Random Forest (GitHub)** How to tune RF parameters in practice?
 Measures of variable importance in random forests
 Compare Rsquared from two different Random Forest models
 OOB Estimate Explained  RF vs LDA
 Evaluating Random Forests for Survival Analysis Using Prediction Error Curve
 Why doesn’t Random Forest handle missing values in predictors?
 How to build random forests in R with missing (NA) values?
 FAQs about Random Forest, More FAQs
 Obtaining knowledge from a random forest
 Some Questions for R implementation, 2, 3
Boosting
Boosting for Better Predictions Boosting Wikipedia Page
 Introduction to Boosted Trees  Tianqi Chen
 Gradient Boosting Machine
 xgboost
 AdaBoost
 CatBoost
Ensembles
 Wikipedia Article on Ensemble Learning
 Kaggle Ensembling Guide
 The Power of Simple Ensembles
 Ensemble Learning Intro
 Ensemble Learning Paper
 Ensembling models with R, Ensembling Regression Models in R, Intro to Ensembles in R
 Ensembling Models with caret
 Bagging vs Boosting vs Stacking
 Good Resources  Kaggle Africa Soil Property Prediction
 Boosting vs Bagging
 Resources for learning how to implement ensemble methods
 How are classifications merged in an ensemble classifier?
Stacking Models
 Stacking, Blending and Stacked Generalization
 Stacked Generalization (Stacking)
 Stacked Generalization: when does it work?
 Stacked Generalization Paper
Vapnik–Chervonenkis Dimension
 Wikipedia article on VC Dimension
 Intuitive Explanantion of VC Dimension
 Video explaining VC Dimension
 Introduction to VC Dimension
 FAQs about VC Dimension
 Do ensemble techniques increase VCdimension?
Bayesian Machine Learning
 Bayesian Methods for Hackers (using pyMC)
 Should all Machine Learning be Bayesian?
 Tutorial on Bayesian Optimisation for Machine Learning
 Bayesian Reasoning and Deep Learning, Slides
 Bayesian Statistics Made Simple
 Kalman & Bayesian Filters in Python
 Markov Chain Wikipedia Page
Semi Supervised Learning
 Tutorial on Semi Supervised Learning
 Graph Based Semi Supervised Learning for NLP
 Taxonomy
 Video Tutorial Weka
 Unsupervised, Supervised and Semi Supervised learning
 Research Papers 1, 2, 3
Optimization

Mean Variance Portfolio Optimization with R and Quadratic Programming
 Algorithms for Sparse Optimization and Machine Learning
 Optimization Algorithms in Machine Learning, Video Lecture
 Optimization Algorithms for Data Analysis
 Video Lectures on Optimization
 Optimization Algorithms in Support Vector Machines
 The Interplay of Optimization and Machine Learning Research
 Hyperopt tutorial for Optimizing Neural Networks’ Hyperparameters