For people who want to practice machine learning, An Introduction to Statistical Learning with Applications in R by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani is a popular textbook choice. It certainly helps that a PDF version of the book is available for free on the authors' website, but the book itself is also an excellent introduction to techniques for statistical learning.
When refreshing my statistical learning skills earlier this year and learning Python for data analysis, the ISLR book was the main reading in the online course that I took. In the past months, I have slowly worked through the book. In parallel, I have worked on an Anki deck that helps me repeat and memorize the book content.
The deck contains about 200 cards covering all 10 chapters, focusing on the terminology and the core content of the book. All cards are tagged per chapter to allow focusing on specific chapters or using the deck while reading along the book. Moreover, each card includes a note with the page number for reference (in case more context is needed).
I hope that this deck is helpful to others who want to get a broad overview of statistical learning techniques. Any feedback is welcome (preferably in the Github repository). I would recommend to use the flashcards as a companion to the book, but not as a replacement. It will be quite difficult to understand the context of the cards without reading the cards (just like it’s impossible to become a fluent speaker of a language by memorizing a stack of vocabulary cards).