Here’s a list of free online books that I’ve come across in areas I find interesting – mathematics, statistics, data science, machine learning, etc.
Inclusion should be taken as “weak endorsement” – I haven’t read all these books but at the very least I believe what they’re doing seems interesting. For now this is just a list but I’ll add descriptions as I get a chance. (Honestly this list exists partially so I don’t have to Google for books whenever I want to find them…)
Last modified January 9, 2021 (!)
Scott Cunningham, Causal Inference: The mixtape
Garrett Grolemund and Hadley Wickham, R for data science
Trevor Hastie, Robert Tibshirani, and Jerome Friedman. Elements of Statistical Learning.
Kieran Healy, Data visualization, a practical introduction
Miguel Hernan and Jamie Robins, Causal Inference: What If.
Rob Hyndman and George Athanasoupoulos, Forecasting: principles and practice
Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani. An Introduction to Statistical Learning.
Alicia A. Johnson, Miles Ott, Mine Dogucu. Bayes Rules! An Introduction to Bayesian Modeling with R (in progress)
Max Kuhn and Julia Silge, Tidy Modeling with R
Max Kuhn and Kjell Johnson, Feature Engineering and Selection: A Practical Approach for Predictive Models
Kevin Murphy, Probabilistic Machine Learning: An Introduction
Cosma Shalizi, Advanced Data Analysis from an Elementary Point of View.
Julia Silge and David Robinson, Text mining with R: A tidy approach
Hadley Wickham, Mastering Shiny
Other lists of books:
Oscar Baruffa’s Big Book of R is a collection of links to books on R.