My first brush with what could be called machine learning was around 2010 with Kevin Gurney’s Artifical Neural Networks, a slim book that must be sorely outdated by now. In fact, this exposure to the material came to me so early that this book served as my introduction to both trigonmetric functions and differential calculus, yet at the time I had no understanding that this curious object the text called “the derivative” was an integral part of calculus. Around that time I learned Python 2.7, though I never attempted to create anything ambitious with this knowledge.

Over the years I have maintained a passing interest in machine learning, and judging by the massive amount of materials on the topic, I am not alone in this interest. Now that I possess more mathematical sophistication, I have endeavoured to return to the subject. Principally, I’ll focus my efforts on reproducing the efforts of David Foster’s Generative Deep Learning, but I’ll be consulting other resources as nessecary.

Enough talk. Let’s get started.