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The StatQuest Illustrated Guide to Machine Learning!!!

I'm a very big fan of Josh Starmer, so once I saw that he was publishing his own book, The StatQuest Illustrated Guide to Machine Learning!!!, I knew that it was a must read!

The book has 12 chapters:

  • Fundamental Concepts in Machine Learning
  • Cross Validation
  • Fundamental Concepts in Statistics
  • Linear Regression
  • Gradient Descent
  • Logistic Regression
  • Naive Bayes
  • Assessing Model Performance
  • Preventing Overfitting with Regularization
  • Decision Trees
  • Support Vector Classifiers and Machines (SVMs)
  • Neural Networks

and while I was familiar with many of the concepts from one of my favourite courses, 02582 Computational Data Analysis, I still learned and refreshed a lot in this book - and it's such a joy seeing Starmer do what he does best: explain statistics and machine learning in a very down-to-earth, illustrative fashion.

I highly recommend this book - if not for the machine learning, then at least for the masterclass in communication of fairly technical and mathematical concepts. If just all course slides were this good...