£111.72

Chapman and Hall/CRC Mathematical Engineering of Deep Learning - Chapman and Hall/CRC

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Description

Master the foundations of modern artificial intelligence with Mathematical Engineering of Deep Learning. Part of the Chapman and Hall/CRC Data Science Series, this book offers a complete and concise overview of deep learning through the precise language of mathematics. It serves as a self-contained resource for understanding the essential background of machine learning and optimization algorithms required to progress into advanced topics. This text guides readers through the core ideas and architectures that drive today's technology. You will explore deep neural networks, convolutional models, and recurrent models, as well as long/short-term memory and the attention mechanism. The content also covers modern developments including transformers, variational auto-encoders, diffusion models, and generative adversarial networks. Whether you are studying reinforcement learning or graph neural networks, this book provides the mathematical framework needed to understand how these complex systems function.

Key Features

Provides a complete and concise overview of deep learning using mathematical language for technical clarity.

Includes a self-contained background on machine learning and optimization algorithms to build a strong foundation.

Covers essential architectures such as deep neural networks, convolutional models, and recurrent models.

Explores advanced concepts including the attention mechanism, transformers, and long/short-term memory.

Detailed coverage of generative models like variational auto-encoders, diffusion models, and GANs.

Extends into specialized fields such as reinforcement learning and graph neural networks.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
03 October 2024
Listed Since
17 March 2024

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