000			02219nam a22002297a 4500
003			OSt
005			20250205120716.0
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020			_a9781774690482
040			_aNISER LIBRARY _beng _cNISER LIBRARY
082			_a53:004.85 _bBOL-M
100			_aBolivar, Nelson
245			_aMachine learning : _ba physicist perspective
260			_aBurlington : _bArcler Press, _c2022
300			_axxii, 242p.
504			_aIncludes bibliographical references and index.
520			_aDeep-learning and machine-learning have gained a significant importance in the last few years. New inventions and discoveries are taking place every day to exploit the concepts of machine-learning technique. The aim of this book is to present the fundamentals of machine-learning with an emphasis on deep-learning, neural networks and physical aspects of machine learning. Design of materials and molecules with desired features is an essential prerequisite for progressing technology in our contemporary societies. This necessitates both the capability to compute precise microscopic characteristics, such as forces, energies and efficient selection of potential energy faces, to attain corresponding macroscopic features. Tools required to achieve the above mentioned goals can be extracted from quantum mechanics, statistical mechanics, and classical physics, respectively. To overcome the challenge of technology integration, significant efforts are being made to speed up quantum physical simulations with the help of machine learning. This evolving interdisciplinary community consists of material scientists, chemists, physicists, computer scientists and mathematicians, coming together to contribute to the exciting field of machine learning and artificial intelligence. This book can be used as a reference material for acquiring fundamentals of machine learning from a physicist's perspective. Moreover, people from all backgrounds can benefit from this introductory book on Machine Learning.
650			_aMachine learning
650			_aComputational physics
856			_3Reviews _uhttps://www.goodreads.com/book/show/90248341-machine-learning#CommunityReviews
942			_2udc _cBK
999			_c35572 _d35572