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<span xml:lang="en">Hands-On Mathematics for Deep Learning: Build a solid mathematical foundation for training efficient deep neural networks</span>

Dawani, Jay

A comprehensive guide to getting well-versed with the mathematical techniques for building modern deep learning architecturesKey FeaturesUnderstand linear algebra, calculus, gradient algorithms, and other concepts essential for training deep neural networksLearn the mathematical concepts needed to understand how deep learning models functionUse deep learning for solving problems related to vision, image, text, and sequence applicationsBook DescriptionMost programmers and data scientists struggle with mathematics, having either overlooked or forgotten core mathematical concepts.

A comprehensive guide to getting well-versed with the mathematical techniques for building modern deep learning architecturesKey...

Hands-On Mathematics for Deep Learning: Build a solid...

Hands-On Mathematics for Deep Learning: Build a solid mathematical foundation for training efficient deep neural networks

Format

Hands-On Mathematics for Deep Learning: Build a solid mathematical foundation for training efficient deep neural networks

Jay Dawani

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