£127.98

Springer Handbook of Deep Learning Applications - Vol 136

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Description

Explore the expansive field of machine learning with the Handbook of Deep Learning Applications, part of the Smart Innovation, Systems and Technologies series. This comprehensive volume covers a wide array of practical implementations and advanced techniques that define modern artificial intelligence. Readers can examine diverse applications including computer vision, natural language processing, and gene expression analysis. The text provides detailed insights into specialized areas such as driverless cars, semantic image segmentation, and brain-computer interfaces. It also addresses technical foundations like big data processing and the construction of GPU-accelerated deep learning frameworks. By focusing on the use of many layers of nonlinear units, this book helps users understand how deep learning functions as an advanced level of machine learning. Whether you are studying arbitrary object recognition or hierarchical deep learning networks used in game-playing, this handbook serves as a technical resource for understanding complex algorithmic structures.

Key Features

Covers diverse applications ranging from vision and natural language processing to gene expression and arbitrary object recognition.

Provides technical depth on specialized systems like driverless cars, semantic image segmentation, and brain-computer interfaces.

Explores advanced data management through big data processing and the development of GPU-accelerated deep learning frameworks.

Examines complex algorithmic structures including hierarchical deep learning networks used as game-playing artefacts.

Delivers insights into deep visual residual abstraction and the mechanics of nonlinear unit layers in machine learning.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
06 March 2019
Listed Since
11 December 2018

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