Writing about ML, data, and things I learn along the way.
Patterns and techniques for building RAG systems with LangGraph, Qdrant, and OpenAI. Covers chunking, hybrid retrieval, query rewriting, and hallucination prevention.
Building a bipartite genre network from the Steam database, projecting it into a weighted graph, running centrality and community detection, and learning why static game properties cannot predict playtime.
Implementing every ML algorithm twice: first from scratch in NumPy, then in PyTorch. From linear regression through CNNs, RNNs, and transformers, with miniprojects on MNIST, CIFAR-10, CelebA, and IMDB.
Techniques for extracting quantitative voice metrics from raw WAV files. Covers pitch tracking, loudness measurement, spectral analysis, and silence detection using Python libraries.