This blog post's topics are remarkably similar to Stanford's Introduction to Statistical Learning's topic order. <snip> Topics include * Overview of s

This blog post's topics are remarkably similar to Stanford's Introduction to Statistical Learning's topic order. <snip> Topics include * Overview of statistical learning * Linear regression * Classification * Resampling methods * Linear model selection and regularization * Moving beyond linearity * Tree-based methods * Support vector machines * Unsupervised learning </snip> source: https://online.stanford.edu/courses/stats216v-introduction-statistical-learning https://online.stanford.edu/courses/stats216v-introduction-s... There is a free (R-lang based) course, which covers this material by Trevor Hastie: https://online.stanford.edu/courses/sohs-ystatslearning-statistical-learning-self-paced https://online.stanford.edu/courses/sohs-ystatslearning-stat... - it's mentioned in the blog post.