Probabilistic Deep Learning: With Python, Keras and Tensorflow Probability - Brossura

Durr, Oliver; Sick, Beate

 
9781617296079: Probabilistic Deep Learning: With Python, Keras and Tensorflow Probability
Brossura
ISBN 10: 1617296074 ISBN 13: 9781617296079
Casa editrice: Manning Pubns Co, 2020

Sinossi

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.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Informazioni sugli autori

Oliver Duerr is professor for data science at the University of Applied Sciences in Konstanz, Germany.

Beate Sick holds a chair for applied statistics at ZHAW, and works as a researcher and lecturer at the University of Zurich, and as a lecturer at ETH Zurich.

Elvis Murina is a research assistant, responsible for the extensive exercises that accompany this book.



Oliver Duerr is professor for data science at the University of Applied Sciences in Konstanz, Germany. Beate Sick holds a chair for applied statistics at ZHAW, and works as a researcher and lecturer at the University of Zurich, and as a lecturer at ETH Zurich. Elvis Murina is a research assistant, responsible for the extensive exercises that accompany this book.

Duerr and Sick are both experts in machine learning and statistics. They have supervised numerous bachelors, masters, and PhD theses on the topic of deep learning, and planned and conducted several postgraduate and masters- level deep learning courses. All three authors have been working with deep learning methods since 2013 and have extensive experience in both teaching the topic and developing probabilistic deep learning models.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Editore
Manning Pubns Co
Data di pubblicazione
2020
Lingua
Inglese
ISBN 10 
1617296074
ISBN 13 
9781617296079
Rilegatura
Copertina flessibile
Numero di pagine
274
Contatto del produttore
non disponibile
Persona responsabile
non disponibile