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"Probabilistic Machine Learning: An Introduction"

Main github repo

Chapter Name Colab for generating figures Supplementary material
1 Introduction Link Link
2 Probability: univariate models Link Link
3 Probability: multivariate models Link Link
4 Statistics Link Link
5 Decision theory Link Link
6 Information theory Link Link
7 Linear algebra Link Link
8 Optimization Link Link
9 Linear discriminant analysis Link Link
10 Logistic regression Link Link
11 Linear regression Link Link
12 Generalized linear models Link Link
13 Neural networks for unstructured data Link Link
14 Neural networks for images Link Link
15 Neural networks for sequences Link Link
16 Exemplar-based methods Link Link
17 Kernel methods Link Link
18 Trees Link Link
19 Learning with fewer labeled examples Link Link
20 Dimensionality reduction Link Link
21 Clustering Link Link
22 Recommender systems Link Link
23 Graph embeddings Link Link