Useful resources for ML PhD students

A collection of resources I’ve found useful during my ML PhD. If you’re starting out or deep in the weeds, hopefully something here saves you some time.

Getting Started & General Advice

• Just Know Stuff: A Guide to an ML PhD — Singlehandedly saved my PhD. If I had spent 100% more time doing what it said, it would not have been wasted.

• How to ML Rebuttal — Practical guidance on writing effective ML paper rebuttals.

Courses & Lectures

• General ML Overview (YouTube Playlist) — A solid video lecture series covering core ML topics at a very high level.

Books

• Probabilistic Machine Learning: Advanced Topics — Comprehensive reference on advanced probabilistic ML.

• Bayesian Computation Book — A good overview of Bayesian methods and computation (Online book).

• Causal Inference for the Brave and True — Online book and hands-on Python-based overview to causal inference.