Technical blog posts about programming, web development, and technology
Yesterday we fit a line to predict numbers. Today, we adapt that same idea for a different kind of question: yes or no. Logistic Regression is the wor...
Day 7 on Dense Embedding — Capturing Semantic Meaning with Vector Representations spent the whole class on the dense half of the embedding world. Toda...
Day 6 on Embeddings — Semantic Similarity, Cosine, and Dense vs Sparse closed with the dense-versus-sparse split and a small Ollama demo. Today we slo...
Three days of fundamentals and we are finally meeting our first real algorithm. Linear Regression is the simplest, oldest, and still one of the most u...
Day 5 wrapped up chunking and PDF processing. Today we go one layer deeper into embeddings themselves, the piece of the pipeline that actually decides...
On Day 2, we met overfitting and underfitting as the two failure modes of ML. Today we put both of them inside one mental model that explains every mo...
On Day 1, we said a model "learns" from examples. But how do we actually know if it learned, or if it just memorised? That single question is what tra...
Day 4 promised PDF processing for today. Before we get there, two more chunking flavours worth meeting first. Sliding chunking and token-based chunkin...
After spending the last few weeks documenting my RAG self-study journey (you can find those posts under the RAG section), I have decided to dive into ...