The Principles of Deep Learning Theory by Daniel A. Roberts, Sho Yaida, and Boris Hanin…
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The Principles of Deep Learning Theory by Daniel A. Roberts, Sho Yaida, and Boris Hanin is now in @ChapterPal's collection. This textbook provides an effective theory of deep learning rooted in theoretical physics, statistical mechanics, and probability theory. Designed for machine learning theorists, mathematically oriented practitioners, and physicists studying neural networks, it assumes a background in multivariable calculus, linear algebra, probability, and basic statistical mechanics concepts such as Gaussian integrals, partition functions, and perturbation expansions. The core subjec
Posted by BURKOV (59.2k followers) 1 days ago · 59 likes · 2.9k views · view the original post on X. Kept by the AI Radar as AI research. Tools mentioned: ChapterPal.
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