Enhancing Deep Learning with Bayesian Inference
This book provides a comprehensive introduction to Bayesian deep learning methods for machine learning researchers and practitioners. It discusses the importance of uncertainty in machine learning, covers numerous methods for uncertainty-aware deep networks, and provides detailed code examples in Python to assist you throughout your exploration.
Offered by
Difficulty Level
Intermediate
Completion Time
12h52m
Language
English
About Book
Who Is This Book For?
This book will cater to researchers and developers looking for ways to develop more robust deep learning models through probabilistic deep learning. You’re expected to have a solid understanding of the fundamentals of machine learning and probability, along with prior experience working with machine learning and deep learning models.
Enhancing Deep Learning with Bayesian Inference
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 12h52m total length
Bayesian Inference in the Age of Deep Learning
Fundamentals of Bayesian Inference
Fundamentals of Deep Learning
Introducing Bayesian Deep Learning
Principled Approaches for Bayesian Deep Learning
Using the Standard Toolbox for Bayesian Deep Learning
Practical considerations for Bayesian Deep Learning
Applying Bayesian Deep Learning
Next Steps in Bayesian Deep Learning
Related Resources
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