wbasener/BayesianML
This is a GitHub repository for our Bayeisan Machine Learning textbook, which includes the PDF for the book and accompanying Python notebooks.
This resource offers a comprehensive textbook and accompanying Python notebooks to introduce Bayesian Machine Learning. It provides theoretical grounding and practical examples, covering how Bayesian methods use prior knowledge for regularization, infer distributions, and quantify prediction uncertainty. It is ideal for students or practitioners looking to deepen their understanding of advanced statistical modeling.
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Use this if you want to learn Bayesian Machine Learning from a practical yet thorough perspective, with hands-on Python examples.
Not ideal if you are looking for a plug-and-play software tool or don't have some background in Python, probability, and basic machine learning.
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Jupyter Notebook
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Apache-2.0
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Last pushed
Jan 25, 2023
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