£107.98

Springer Concise Guide to Quantum Machine Learning Book

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Description

Expand your technical knowledge with the Concise Guide to Quantum Machine Learning. Published by Springer as part of the Machine Learning: Foundations, Methodologies, and Applications series, this book provides a targeted look at the intersection of quantum computing and artificial intelligence. This text is designed for readers interested in the evolving landscape of computer science and AI. By focusing on the fundamental methodologies and practical applications within the field, it serves as a specialized resource for those studying advanced computing and internet technologies. Whether you are exploring machine learning foundations or looking to understand how quantum mechanics influences modern algorithms, this guide offers a structured approach to a complex subject. This book belongs to a respected series known for academic rigor, making it a reliable addition to your professional or educational library. It is an essential resource for students and professionals navigating the specialized category of AI and machine learning.

Key Features

Part of the Machine Learning: Foundations, Methodologies, and Applications series for structured learning.

Published by Springer, a leading name in academic and technical publishing.

Focused content covering the convergence of quantum computing and machine learning technologies.

Designed for readers interested in computer science, AI, and advanced internet computing.

Provides a specialized look at the methodologies used in modern quantum machine learning.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
17 December 2023
Listed Since
21 November 2023

Barcode

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