This repository contains Jupyter Notebooks illustrating various clustering techniques, culminating in the Dirichlet Process Method. A recording talking through the notebooks is available here: https://ukri.zoom.us/rec/play/7pElJO36qz03GdSUtASDU6N-W9S_LP2s0nQc-PEEzBq9ACYHZ1v0YbsUZeKagSyBeoMlZ_IuFGNXKzyN?startTime=1590420233000.
For more theoretical background see ClusteringSlides.pdf or consult A Concise Introduction to Machine Learning. Note that in the second print run the book was printed in grayscale. This was noticed, but some were already sold. If you are one of the unlucky ones not to have a colour copy, you can email Randi Cohen (randi.cohen@taylorandfrancis.com) to receive a corrected copy.
Suggested order to learn from this:
- 1DMixture_numpy_random
- 1DMixture_scipy_stats
- 1_GaussianMixture
- 2_InferGaussianMixture
- 3_BayesianMixture
- 4_InferBayesianMixture
- 5_ChineseRestaurantProcess
- 6_sklearnDirichletProcess
- 7_InferDirichletProcess