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40+ Modern Tutorials Covering All Aspects of Machine Learning

This list of lists contains books, notebooks, presentations, cheat sheets, and tutorials covering all aspects of data science, machine learning, deep learning, statistics, math, and more, with most documents featuring Python or R code and numerous illustrations or case studies. All this material is available for free, and consists of content mostly created in 2019 and 2018, by various top experts in their respective fields. A few of these documents are available on LinkedIn: see last section on how to download them. 

Below are the first two sections.

General References

  • Free Deep Learning Book (639 pages) by Prof. Gilles Louppe
  • Python Crash Course (562 pages) by Eric Matthes
  • Free Book: Applied Data Science (141 pages) - Columbia University
  • Data Science in Practice
  • Machine Learning 101 - By Jason Mayes, Google
  • The Ultimate guide to AI, Data Science & Machine Learning
  • Free Handbooks for Data Science Professionals
  • Free Book: Natural Language Processing with Python
  • Data Visualization Resources
  • Textbook: Probability Course - Harvard University
  • Textbook: The Math of Machine Learning - Berkeley University
  • Comprehensive Guide to Machine Learning - Berkeley University
  • Free Book: Foundations of Data Science - by Microsoft Research
  • Comprehensive Guide on Machine Learning - by J.P. Morgan
  • Gentle Approach to Linear Algebra - by Vincent Granville

Data Science Central Books, Booklets and References

  • Statistics: New Foundations, Toolbox, and Machine Learning Recipes
  • Deep Learning and Computer Vision with CNNs
  • Getting Started with TensorFlow 2.0
  • Classification and Regression in a Weekend
  • Online Encyclopedia of Statistical Science
  • Azure Machine Learning in a Weekend
  • Enterprise AI - An Application Perspective
  • Applied Stochastic Processes
  • Comprehensive Repository of Data Science and ML Resources
  • Foundations of ML and Data Science for Developers
  • Elegant Representation of Forward/Back Propagation in Neural Networks
  • Learning the Math of Data Science

To access all these documents and more, follow this link.

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