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Springer Machine Learning in Molecular Sciences, Vol 36

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Description

Explore the intersection of artificial intelligence and chemical research with Machine Learning in Molecular Sciences, Volume 36. Published by Springer as part of the Challenges and Advances in Computational Chemistry and Physics series, this volume addresses modern developments in the field. This academic text provides specialized knowledge for researchers and professionals working within the computational sciences. It focuses on how machine learning techniques are applied to solve complex problems in molecular science, offering a deep look into current methodologies and technical progress. Whether you are studying computational chemistry or physics, this volume serves as a significant resource for understanding how data-driven approaches are changing the landscape of molecular research. By integrating machine learning with traditional computational methods, this work supports the ongoing evolution of chemical physics. It is an essential addition to any academic or professional library focused on computer science, AI, and the advanced study of molecular systems.

Key Features

Part of the Challenges and Advances in Computational Chemistry and Physics series, specifically volume 36.

Focuses on the integration of machine learning within the molecular sciences.

Published by Springer, a leading name in academic and scientific literature.

Provides technical insights into computational chemistry and physics applications.

Designed for professionals and students in the fields of AI and machine learning.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
03 October 2024
Listed Since
04 October 2024

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