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A “Small” Learning List for ML Engineers

Ever since I decided that I want to be a machine learning engineer, I have never stopped feeling overwhelmed by the topics I need to learn and the concepts I need to cover. It's absolutely staggering, both in depth and breadth.

The resources are many. so many choices, so many options, so many books, articles, and more. It's very difficult to choose what is best for you. Every time I sit down to learn, I am bombarded with these resources.

This has made me pause and give up many times. When I start reading about a topic, I often come across related concepts or ideas that catch my attention, causing me to shift focus. This constant switching makes it difficult to retain progress, leaving me feeling as though I'm not learning effectively. This happens a lot.

So I decided to write down only what felt necessary and put it all in one place. The goal was to keep the list short, doable, and focused on resources that are widely recommended and actually worth finishing. As I complete each book or course, I plan to add my own notes alongside it, so this slowly becomes more than just a list.

What you’re looking at below is my personal, evolving list of resources. This isn’t meant to be exhaustive or trendy. It’s simply a collection of things that, in my experience, explain concepts clearly and reward patience. I’ll keep updating it over time as I find better ways to learn.

Concepts

  1. Introduction to Statistical Learning (ISLR)
  2. ML Engineering - Andy Burkov:
  3. Dive into Deep Learning
  4. Deep Learning with Python - Francois Chollet
  5. Hands-on Large Language Models
  6. Build a LLM from Scratch.

Engineering

  1. DDIA - Designing Data Intensive Applications
  2. CPU Land
  3. Designing ML Systems - Chip Huyen:
  4. Reliable Machine Learning
  5. Deep Learning at Scale
  6. Machine Learning Engineering Open Book by Stas Bekman
  7. How to Scale your Model
  8. The Smol Training Playbook

Courses

  1. Neural Networks: Zero to Hero - Andrej Karpathy
  2. CS224W: ML with Graphs
  3. Transformers Model - Hugging Face Course

Changelog:

  • Jan 14, 2025: Created the initial list of resources
  • Feb 15, 2025: Updated progress on "Hands-on Large Language Models"
  • Nov 10, 2025: Added "How to Scale your Model" and "The Smol Training Playbook"
  • Dec 23, 2025: Added Machine Learning Engineering Open Book by Stas Bekman