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Springer Deep Learning: Concepts and Architectures Book

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Description

Explore the fundamental principles of deep learning with this comprehensive guide from Springer. Part of the Studies in Computational Intelligence series, this book introduces readers to the core concepts of the deep learning paradigm and how it enables automatic mechanisms for structural knowledge representation. The text examines various multilayer architectures that produce meaningful pieces of knowledge. It explains how structural developments in these architectures have become necessary for delivering competitive solutions to real-world problems. By studying how architectural advancements support detailed learning processes, readers gain insight into the practical applications and evolution of modern AI and machine learning technologies.

Key Features

This Springer publication covers fundamental concepts of deep learning and structural knowledge representation.

The book discusses multilayer architectures that produce tangible and functionally meaningful pieces of knowledge.

Readers learn how structural developments in deep learning provide competitive solutions to real-world problems.

Part of the Studies in Computational Intelligence series, volume 866, providing specialized academic depth.

The text demonstrates how architectural developments within deep learning settings support detailed processes.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
13 November 2019
Listed Since
22 August 2019

Barcode

No barcode data available

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