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Probabilistic Reasoning in Neural Networks: A Dev Guide
Learn to build neural networks that reason under uncertainty using Bayesian methods, MC Dropout, and deep ensembles. Practical PyTorch examples included.
Learn to build neural networks that reason under uncertainty using Bayesian methods, MC Dropout, and deep ensembles. Practical PyTorch examples included.
Master exact inference algorithms for Bayesian networks including variable elimination and junction trees with practical Python implementations.