Introductory Machine Learning Course Material

From my 2018 Make+Think+Code Visual, Audio, and Speech workshops at PNCA.

TAGS: machine learning,ml5,tensorflow,javascript,p5js,magenta

In agreeing to teach a Machine Learning course at PNCA's Make+Think+Code program, I realized I had to learn it myself. This is my course material - a set of notes that became a series of workshops, using ML5.js, Papers[ace, ML4A_OFX for OpenFrameworks, and a little bit of Tensorflow / Magenta.

The material is based heavily off Gene Kogan's excellent Neural Aesthetics course at ITP, as well as some great work from Kyle Mcdonald, Distill's Collab Notebooks, and many more.

I don't claim to be an expert in the field, but definitely a dedicated enthusiast. If you are experienced in the field and come across this, I'd love your feedback, corrections, etc. And if you're just getting started, I hope the material is helpful to you!

The material is divided into 3 sections:

I like dropbox paper, because it retains the ability to modify, comment, and version the material, gives a nice uncluttered visual presentation, and allows you to easily turn things into slides with the click of the "present" button.

Hope it's helpful!