Understanding Deep Learning

Prince, Simon J. D.

ISBN 10: 0262048647 / ISBN 13: 9780262048644

Verlag: MIT Press, 2023

Beschreibung

Ships SAME or NEXT business day. We Ship to APO/FPO addr. Choose EXPEDITED shipping and receive in 2-5 business days within the United States. See our member profile for customer support contact info. We have an easy return policy.

Bestandsnummer des Verkäufers 55144790

Bibliografische Details

• Titel: Understanding Deep Learning
• Verlag: MIT Press
• Erscheinungsjahr: 2023
• Sprache: Englisch
• ISBN-10: 0262048647
• ISBN-13: 9780262048644
• Einband: Hardcover
• Zustand: Like New

Über diesen Titel

Inhaltsangabe

An authoritative, accessible, and up-to-date treatment of deep learning that strikes a pragmatic middle ground between theory and practice.

Deep learning is a fast-moving field with sweeping relevance in today’s increasingly digital world. Understanding Deep Learning provides an authoritative, accessible, and up-to-date treatment of the subject, covering all the key topics along with recent advances and cutting-edge concepts. Many deep learning texts are crowded with technical details that obscure fundamentals, but Simon Prince ruthlessly curates only the most important ideas to provide a high density of critical information in an intuitive and digestible form. From machine learning basics to advanced models, each concept is presented in lay terms and then detailed precisely in mathematical form and illustrated visually. The result is a lucid, self-contained textbook suitable for anyone with a basic background in applied mathematics.

• Up-to-date treatment of deep learning covers cutting-edge topics not found in existing texts, such as transformers and diffusion models
• Short, focused chapters progress in complexity, easing students into difficult concepts 
• Pragmatic approach straddling theory and practice gives readers the level of detail required to implement naive versions of models
• Streamlined presentation separates critical ideas from background context and extraneous detail
• Minimal mathematical prerequisites, extensive illustrations, and practice problems make challenging material widely accessible 
• Programming exercises offered in accompanying Python Notebooks 

Über die Autorin bzw. den Autor

Simon J. D. Prince is Honorary Professor of Computer Science at the University of Bath and author of Computer Vision: Models, Learning and Inference. A research scientist specializing in artificial intelligence and deep learning, he has led teams of research scientists in academia and industry at Anthropics Technologies Ltd, Borealis AI, and elsewhere.