Browse by topic

Every note belongs to a category. Pick one to see its full list of chapters in the order they were written — or pick across every note at once →.

Storage and Streaming

Storage formats, streaming, object stores, relational databases.

6 items Read

Math for ML

Linear algebra, probability, statistics, calculus, information theory, and optimization — the math the rest of the site leans on.

6 items Read

Classical ML

sklearn, boosting, clustering, feature engineering, model evaluation, A/B testing, interpretability, fairness.

4 items Read

Deep Learning

PyTorch, MLP/CNN/RNN, model compression, distillation, RL, generative models.

12 items Read

Time Series

Data preparation, forecasting models, deep learning, foundation models, evaluation, maintenance.

19 items Read

LLM

Transformer architecture, the generation loop, prompt engineering, structured outputs, agent patterns.

31 items Read

Embeddings and Retrieval

Embeddings, similarity and nearest-neighbor search, ANN indexes and vector databases, sparse and hybrid retrieval, chunking, reranking, and the search lineage from BoW to modern embedding models.

9 items Read

Econometrics

Endogeneity, IV, RDD, panel data, causal ML.

15 items Read

ML Systems

How machine-learning algorithms actually run on hardware: GPUs, CUDA and C++, memory and parallelism, kernels, numerical computing, LLM inference and serving, distributed systems, and performance engineering.

9 items Read