Enhancing deep learning with Bayesian inference : create more powerful, robust deep learning systems with Bayesian deep learning in Python

Enhancing deep learning with Bayesian inference create more powerful, robust deep learning systems with Bayesian deep learning in Python

Develop Bayesian Deep Learning models to help make your own applications more robust. Key Features Gain insights into the limitations of typical neural networks Acquire the skill to cultivate neural networks capable of estimating uncertainty Discover how to leverage uncertainty to develop more robus...

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Detalles Bibliográficos
Otros Autores: Benatan, Matt, author (author), Gietema, Jochem, author, Schneider, Marian, author
Formato: Libro electrónico
Idioma:Inglés
Publicado: Birmingham, England : Packt Publishing Ltd [2023]
Edición:1st ed
Materias:
Deep learning (Machine learning) > Mathematical models.
Neural networks (Computer science) > Mathematical models.
Bayesian field theory.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009755146806719
Tabla de Contenidos:
  • Table of Contents 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.

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