A free Stanford Lagunita self-paced course built around the textbook An Introduction to Statistical Learning with Applications in R, covering the statistical methods behind modern machine learning with R labs. Video lectures and notes accompany the book.

Commenters point to it as a free, self-paced companion to the ISLR book that explains what the algorithms are doing under the hood, with R labs included.

On Reddit (2)

1. Recommendscookiemonsterxr/learnmachinelearning2017in “I'm sorry if this isn't the right place for this but how do you help yourself when you get overwhelmed?”

   I know how you feel. I learned a lot of this throughout the past 5-6 years. Now I have to review and learn 'new' technology. I got really overwhelmed and ended up getting nothing done when I was obsessing what to learn and compiling a ridiculous amount of resources. I agree with what others are…

2. Recommendschalupapar/learnmachinelearning2017in “Need some help to understand The Elements of Statistical Learning.”

   I think the book is quite readable. If you were a beginner I would recommend you read the whole book. Note there are video lectures (and exercises) for the book: https://lagunita.stanford.edu/courses/HumanitiesSciences/StatLearning/Winter2016/about I suggest you watch the videos while reading the…

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