Learning Machine Learning!

One of the classes that I took this year was Dr. Daniela Witten’s Machine Learning class at the University of Washington. (Yes, Daniela Witten — the one who wrote “An Introduction to Statistical Learning”) And boy, it was the BEST course I have had the pleasure to take! The class was LEGENDARY. I just couldn’t stop talking about the happenings of the class, the concepts, and just how well they were explained (and by extension, how well did I understand them and how well could I explain them to others), the assignment problems that forced me to think differently, and the feeling of satisfaction that came at the end of every assignment that I completed. I had been going on and on with everyone I talked to, about this class that I took and that it was perfectly splendid! People with little to no interest in Machine Learning were kind of tired of listening to me blab about it. And so I thought, why not talk about it with people interested in hearing what I wish to say!

And so, I decided to do a blog series. In this series, I will mostly blog about the concepts taught during the class, applications in R, problems encountered, assignments, and almost everything else about this amazing class I took. XD

The course closely followed “An Introduction to Statistical Learning: with Applications in R” and this blog series will also consist of my notes on the ISLR book.

This post works as the home page of this series and I will update this every time I post some new blogs in this series. It will be easier for me to organize the blogs and easier for you all to navigate through. Win-win!!