£113.94

Springer Machine Learning-Augmented Spectroscopies Book

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Description

Explore the intersection of advanced technology and material science with Machine Learning-Augmented Spectroscopies for Intelligent Materials Design. Published by Springer as part of the Springer Theses series, this book addresses modern approaches to materials design through the lens of artificial intelligence and machine learning. Designed for researchers and students in computer science and AI, this text provides a focused look at how machine learning can enhance spectroscopic data and material analysis. It serves as a specialized resource for those studying the application of computing and internet technologies within the field of materials science. Whether you are working in AI research or looking to understand the role of automated data processing in spectroscopy, this Springer publication offers a dedicated academic perspective on intelligent design methodologies.

Key Features

Part of the respected Springer Theses collection for academic research.

Focuses on the application of machine learning within spectroscopic fields.

Provides specialized knowledge for intelligent materials design processes.

Targets professionals in the AI and machine learning computer science sectors.

Offers a technical perspective on modern computing and internet applications.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
08 October 2023
Listed Since
10 September 2023

Barcode

No barcode data available

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