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Springer Deep Learning: Algorithms and Applications - Springer 865

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Description

This comprehensive guide from Springer presents a wealth of deep-learning algorithms and demonstrates their practical design process. Written for readers seeking hands-on knowledge of analysing, designing, and deploying deep learning solutions to real-world problems, the book covers a wide range of algorithms and their applications across diverse fields including imaging, seismic tomography, smart grids, surveillance and security, and healthcare. The content emphasises the importance of aligning deep learning approaches with the essential characteristics of learning encountered in practical problem-solving, making it an essential resource for professionals and students working with machine learning technologies.

Key Features

Springer's Studies in Computational Intelligence series volume 865 provides expert-level coverage of deep learning methodologies and practical implementations.

The book demonstrates the design process for deep-learning algorithms with real-world applications spanning imaging, seismic tomography, smart grids, and healthcare sectors.

Comprehensive exploration of deep learning's algorithmic paradigms equips readers with knowledge for deploying solutions to complex, practical problems.

Coverage includes surveillance, security, and healthcare applications, showing how deep learning algorithms address modern industry challenges.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
04 November 2020
Listed Since
08 October 2020

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No barcode data available

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