*This book provides easy-to-apply code and uses popular frameworks to keep you focused on practical applications.*

**Author**: Oliver Duerr

**Publisher:** Manning Publications

**ISBN:** 9781617296079

**Category:** Computers

**Page:** 296

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*This book provides easy-to-apply code and uses popular frameworks to keep you focused on practical applications.*

**Author**: Oliver Duerr

**Publisher:** Manning Publications

**ISBN:** 9781617296079

**Category:** Computers

**Page:** 296

**View:** 897

*The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.*

**Author**: Kevin P. Murphy

**Publisher:** MIT Press

**ISBN:** 9780262018029

**Category:** Computers

**Page:** 1067

**View:** 489

*Introduction to probabilistic deep learning This chapter covers ▫ What is a
probabilistic model? ▫ What is deep learning and when do you use it? ▫
Comparing traditional machine learning and deep learning approaches for
image ...*

**Author**: Beate Sick

**Publisher:** Simon and Schuster

**ISBN:** 9781638350408

**Category:** Computers

**Page:** 296

**View:** 550

*A central insight from psychological studies on human eye movements is that eye movement patterns are highly individually characteristic.*

**Author**: Ahmed Abdelwahab

**Publisher:**

**ISBN:** OCLC:1193146739

**Category:**

**Page:**

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*Cram101 Textbook Outline notebooks have been designed so you can get the most out of your class and study time.*

**Author**: Cram101 Publishing

**Publisher:** Cram101

**ISBN:** 1490227636

**Category:** Machine learning

**Page:** 260

**View:** 190

*This second edition has been substantially expanded and revised, incorporating many recent developments in the field.*

**Author**: Kevin P. Murphy

**Publisher:** MIT Press

**ISBN:** 9780262361019

**Category:** Computers

**Page:** 1292

**View:** 877

*New to this edition: Complete re-write of the chapter on Neural Networks and Deep Learning to reflect the latest advances since the 1st edition.*

**Author**: Sergios Theodoridis

**Publisher:** Academic Press

**ISBN:** 9780128188040

**Category:** Computers

**Page:** 1160

**View:** 727

*Later in this dissertation, I will present my works on designing probabilistic models in combination with deep learning methods for representing sequential data.*

**Author**: Ghazal Fazelnia

**Publisher:**

**ISBN:** OCLC:1128160871

**Category:**

**Page:**

**View:** 462

*Probability is the bedrock of machine learning.*

**Author**: Jason Brownlee

**Publisher:** Machine Learning Mastery

**ISBN:**

**Category:** Computers

**Page:** 312

**View:** 871

*This is the first text on pattern recognition to present the Bayesian viewpoint, one that has become increasing popular in the last five years.*

**Author**: Christopher M. Bishop

**Publisher:** Springer Verlag

**ISBN:** 0387310738

**Category:** Computers

**Page:** 738

**View:** 436

*Second, we introduce hierarchical implicit models (HIMs). HIMs combine the idea of implicit densities with hierarchical Bayesian modeling, thereby defining models via simulators of data with rich hidden structure.*

**Author**: Dustin Tran

**Publisher:**

**ISBN:** OCLC:1222808921

**Category:**

**Page:**

**View:** 159

*Proceedings of the annual Conference on Uncertainty in Artificial Intelligence, available for 1991-present.*

**Author**: Daphne Koller

**Publisher:** MIT Press

**ISBN:** 9780262013192

**Category:** Computers

**Page:** 1231

**View:** 758

*This book provides a straightforward look at the concepts, algorithms and advantages of Bayesian Deep Learning and Deep Generative Models.*

**Author**: Lucas Pinheiro Cinelli

**Publisher:** Springer

**ISBN:** 3030706788

**Category:** Technology & Engineering

**Page:** 165

**View:** 761

*With this book, you'll explore key approaches to one-shot learning, such as metrics-based, model-based, and optimization-based techniques, all with the help of practical examples.*

**Author**: Shruti Jadon

**Publisher:** Packt Publishing Ltd

**ISBN:** 9781838824877

**Category:** Computers

**Page:** 156

**View:** 200

*What you will gain from this book: * A deep understanding of how Deep Learning works * A basics comprehension on how to build a Deep Neural Network from scratch Who this book is for: * Beginners who want to approach the topic, but are too ...*

**Author**: Pat Nakamoto

**Publisher:** Createspace Independent Publishing Platform

**ISBN:** 1722147776

**Category:**

**Page:** 148

**View:** 149

*The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.*

**Author**: Ian Goodfellow

**Publisher:** MIT Press

**ISBN:** 9780262035613

**Category:** Computers

**Page:** 775

**View:** 541

*New technologies such as the Python PyMC library now make it possible to largely abstract Bayesian inference from deeper mathematics.Bayesian Methods for Hackers is the first book built upon this approach.*

**Author**: Cameron Davidson-Pilon

**Publisher:** Addison-Wesley Professional

**ISBN:** 0133902838

**Category:** Computers

**Page:** 320

**View:** 136