prml

Why we included this project

Christopher Bishop's Pattern Recognition and Machine Learning is the standard text most people work through to learn classical machine learning, and this repository turns it into something you can actually run. The notebooks are organized by chapter and topic, with implementations of logistic regression, Gaussian mixtures, variational inference, MCMC sampling, PCA, HMMs, and other core algorithms, plus code that redraws many of the figures from the book. Several notebooks are deliberately kept minimal so the math stays visible instead of being buried under library calls. That makes it a useful companion for anyone going through the textbook, whether you are teaching it, self-studying, or just refreshing the foundations of Bayesian statistics before moving on to modern deep learning.