Curated Resources

Links

The courses, tools, and reading I recommend to anyone learning AI engineering and research.

Learn the fundamentals

Where to build real intuition for how modern AI works.

Neural Networks: Zero to Hero (Karpathy)

Build backprop, makemore, and a GPT from scratch. The single best on-ramp.

3Blue1Brown: Neural Networks

Visual intuition for what gradient descent and attention are doing.

fast.ai: Practical Deep Learning

Top-down, code-first deep learning that gets you shipping early.

The Illustrated Transformer

The clearest visual walkthrough of attention and the Transformer block.

Build & ship

The tools I reach for when building AI products.

Hugging Face

Models, datasets, and transformers. The hub for applied ML.

PyTorch

My primary framework for research and training.

LangChain / LlamaIndex docs

Reference for RAG plumbing: chunking, retrieval, reranking.

Vercel

How this site and most of my front-ends ship.

Stay current

Where the field moves faster than any textbook.

arXiv: cs.LG / cs.CL

Primary source for new ML research, before it hits the news.

Papers with Code

Papers linked to runnable implementations and leaderboards.

The Batch (DeepLearning.AI)

Weekly, signal-over-noise summary of what matters.

Import AI (Jack Clark)

Thoughtful weekly read on AI progress and its implications.