krasserm/bayesian-machine-learning
A collection of Jupyter notebooks teaching Bayesian machine learning methods through implementations in NumPy, SciPy, scikit-learn, GPy, and PyMC3.
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This repository provides educational notebooks on Bayesian machine learning concepts and implementations. It covers topics such as Bayesian linear regression, Gaussian processes for regression and classification, and variational autoencoders. Each notebook includes implementations both from scratch using NumPy/SciPy and using established ML libraries like scikit-learn and GPy.