<story><title>An Introduction to Statistical Learning with Applications in Python</title><url>https://www.statlearning.com</url></story><parent_chain></parent_chain><comment><author>TheAlchemist</author><text>Off topic, but it&amp;#x27;s very interesting to observe the ratio of upvotes &amp;#x2F; comments.&lt;p&gt;On any given chatGPT topic, there are hundreds of comments usually. Here, so far 100 upvotes, only 7 comments.&lt;p&gt;The book looks great - and given the authors, it almost certainly is (I will buy it for sure). It makes me think though about the state of &amp;#x27;ML &amp;#x2F; AI &amp;#x2F; Data Science&amp;#x27; - and the cynic part of me thinks that this upvotes &amp;#x2F; comments ratio kind of reflects the fact that most people interested in AI hype have not really touched a lot of underlying concepts and don&amp;#x27;t have any deeper understanding of maths &amp;#x2F; stats behind.&lt;p&gt;PS. That being said, I didn&amp;#x27;t do a meaningful comment on the link topic neither.</text></comment>
<story><title>An Introduction to Statistical Learning with Applications in Python</title><url>https://www.statlearning.com</url></story><parent_chain></parent_chain><comment><author>srvmshr</author><text>This is an update to a very popular text which was originally in R. Professors Hastie &amp;amp; Tibshirani are leading educators in statistical learning. They also have a video course following these notes in Stanford Online. Very highly recommended if learning theoretical aspects of classical ML</text></comment>