Mathematical Foundations of Deep Learning by Xiaojing Ye (.PDF)
File Size: 10 MB
Mathematical Foundations of Deep Learning: Theory and Algorithms by Xiaojing Ye
Requirements: .PDF reader, 10 MB | True PDF
Overview: Mathematical Foundations of Deep Learning offers a comprehensive and rigorous treatment of the mathematical principles underlying modern Deep Learning. The book spans core theoretical topics, from the approximation capabilities of deep neural networks and the theory and algorithms of optimal control and Reinforcement Learning integrated with Deep Learning techniques to contemporary generative models that drive today’s advances in Artificial Intelligence. Designed as both a textbook for graduate and advanced undergraduate students as well as a long-term reference, this volume aims to equip students with a solid mathematical understanding of Deep Learning while serving researchers, scientists, and engineers seeking a principled framework for developing and analyzing modern Artificial Intelligence systems.
Genre: Non-Fiction > Tech & Devices
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