Description
Grokking Bayes teaches Bayesianism through clear explanations, rich illustrations, and relatable examples. You’ll first build an intuition, and then translate that intuition into working code with Python tools like the PyMC library and ArviZ package. Along the way, you’ll explore how Bayesian ideas connect to modern AI, from uncertainty-aware deep learning to LLM applications.
Throughout, the book focuses on the skills for making better decisions: you’ll go from inference, to Bayesian decision theory, and even experimental design. Whether you’re a data scientist, AI practitioner, or curious learner, Grokking Bayes will give you the tools to make smarter decisions without needing to rely on long-run frequencies or reams of data without drowning you in probability theory and abstract math.
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