Probabilistic Deep Learning with Python

by Randy Moore in , on October 22, 2020
Wish List
$29.99 – Purchase Excluding 10% tax

has been added to your cart!

have been added to your cart!

Book Description

Probabilistic Deep Learning with Python shows how probabilistic deep learning models gives readers the tools to identify and account for uncertainty and potential errors in their results.

Starting by applying the underlying maximum likelihood principle of curve fitting to deep learning, readers will move on to using the Python-based Tensorflow Probability framework, and set up Bayesian neural networks that can state their uncertainties.

Contents

PART 1 BASICS OF DEEP LEARNING

1 Introduction to probabilistic deep learning
2 Neural network architectures
3 Principles of curve fitting

PART 2 MAXIMUM LIKELIHOOD APPROACHES FOR PROBABILISTIC DL MODELS
4 Building loss functions with the likelihood approach
5 Probabilistic deep learning models with TensorFlow Probability
6 Probabilistic deep learning models in the wild

PART 3 BAYESIAN APPROACHES FOR PROBABILISTIC DL MODELS
7 Bayesian learning
8 Bayesian neural networks

Book Details

  • Title: Probabilistic Deep Learning with Python
  • Length: 297 pages
  • Edition: 1
  • Publisher: Manning Publications
  • Publication Date: 2020-06-09
  • ISBN-10: 1617296074
  • ISBN-13: 9781617296079
  • Sales Rank: #565182 (See Top 100 Books)
Wish List
$29.99 – Purchase Excluding 10% tax

has been added to your cart!

have been added to your cart!

0 Sale

Share Now!

Release Information

  • Price
    :

    $29.99

  • Released
    :

    October 22, 2020

  • Last Updated
    :

    October 22, 2020

Share Your Valuable Opinions

You must log in to submit a review.