The Principles of Deep Learning Theory: An Effective Theory Approach to Understanding Neural Networks

Yaida, Sho: - Sho Yaida is a research scientist at Meta AI. Prior to joining Meta AI, he obtained his PhD in physics at Stanford University and held postdoctoral positions at MIT and at Duke University. At Meta AI, he uses tools from theoretical physics to understand neural networks, the topic of this book.

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Editie: Hardcover

Nr. pagini: 472

Cod: BRT9781316519332

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The Principles of Deep Learning Theory: An Effective Theory Approach to Understanding Neural Networks

De (autor): Daniel A. Roberts

The Principles of Deep Learning Theory: An Effective Theory Approach to Understanding Neural Networks

De (autor): Daniel A. Roberts

Descrierea produsului

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Artificial Intelligence Engines: A Tutorial Introduction to the Mathematics of Deep Learning - James V. Stone

Inside Deep Learning: Math, Algorithms, Models - Edward Raff

Machine Learning with Neural Networks: An Introduction for Scientists and Engineers - Bernhard Mehlig

Neural Networks and Deep Learning: A Textbook - Charu C. Aggarwal

Deep Learning: Fundamentals of Deep Learning for Beginners - Rudolph Russell

Mathematical Aspects of Deep Learning - Philipp Grohs

Deep Learning for Physics Research - Martin Erdmann

The Math of Neural Networks - Michael Taylor

Deep Learning Architectures: A Mathematical Approach - Ovidiu Calin

Deep Learning from the Basics: Python and Deep Learning: Theory and Implementation - Koki Saitoh

Python Machine Learning: A Crash Course for Beginners to Understand Machine learning, Artificial Intelligence, Neural Networks, and Deep Learni - Josh Hugh Learning

Deep Learning and the Game of Go - Max Pumperla

Hands-On Graph Neural Networks Using Python: Practical techniques and architectures for building powerful graph and deep learning apps with PyTorch - Maxime Labonne

A Generative Journey to AI: Mastering the foundations and frontiers of generative deep learning (English Edition) - Toni Ramchandani

Deep Learning with R, Second Edition - Francois Chollet

Practical Deep Learning: A Python-Based Introduction - Ron Kneusel

Deep Learning for Vision Systems - Mohamed Elgendy

Deep Learning: A Visual Approach - Andrew Glassner

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Clergy Retirement - Daniel A. Roberts

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