Machine Learning Engineer

Mathematics

Intuition for linear algebra and calculus: the picture before the formula.

Data Science & ML

The foundations of statistical learning; free, with a Python edition.

Data Science & ML

A fast, hands-on course that ties the concepts together.

Data Science & ML

Overfitting, cross-validation, ROC: reinforced with visual explainers.

Data Science & ML

Fitting classical models on real data, through one shared interface.

Data Science & ML

Measuring your model against everyone else's on the same data.

Data Science & ML

Deep learning top-down: a working model first, the theory after.

Data Science & ML

Writing a language model piece by piece: attention, training, fine-tuning.

AI · Models & Assistants

Pretrained models, datasets and libraries, so you need not train from scratch.

AI · Models & Assistants

Running open-weight models on your own machine with one command.

AI · Models & Assistants

From prototype to service: high-throughput LLM inference.

AI · RAG, Embeddings & Vectors

Connecting a model to your own documents: retrieval-augmented generation.

AI · Agents & Infrastructure

Testing whether a change made the model better or worse.

AI · Agents & Infrastructure

Observability in production: prompts, cost and quality in one place.