Over the past several months I've worked my way through every chapter and excercise of this book, starting from very basic questions -- "what is a function?, what do one-to-one and onto mean?" -- and building the foundation to answer more interesting questions -- *"how can we use SVD factorization and PCA to implement a facial recognition algorithm?", "how do QR factorization, hill climbing, and linear programming compare as machine learning algorithms for a breast cancer data set"

Because it's fun :) Because I see huge potential for data science to have a positive impact in international development and bottom of the pyramid entrepreneurship.
That's what I want to do, and this is an important step. It's one thing to import 'scikit-learn' and call 'RandomForest' and another to understand how it works. I'd like to understand how it works, so that I can not just use it, but use it well. Next up, heavy duty stats.