Machine Learning & Deep Learning Tutorials

• This repository contains a topic-wise 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

• 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
  • Cross Validation
  • Bootstraping
• Deep Learning
  • Frameworks
  • Feed Forward Networks
  • Recurrent Neural Nets, LSTM, GRU
  • Restricted Boltzmann Machine, DBNs
  • Autoencoders
  • Convolutional Neural Nets
  • Graph Representation Learning
• Natural Language Processing
  • Topic Modeling, LDA
  • Word2Vec
• 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

Introduction

• Machine Learning Course by Andrew Ng (Stanford University)

• AI/ML YouTube Courses

• Curated List of Machine Learning Resources

• In-depth 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

• Grokking Machine Learning

Interview Resources