000			01947nam a22002657a 4500
005			20260708164918.0
008			260708s2022 |||||||| |||| 00| 0 eng d
020			_a9781032193571
040			_cPK-LaUMT
082			_a006.31 _bMAC-
245	0	0	_aMachine learning for decision sciences with case studies in Python / _cS. Sumathi . . . [et al.]
260			_aBoca Raton : _bCRC Press, _c2024
300			_axxi, 454 p.
500			_aIncludes bibliographical references and index.
520			_a"This book provides a detailed description of machine learning algorithms in Data Analytics, Data Science Lifecycle, Python for Machine Learning, Linear Regression, Logistic Regression and so forth. It addresses the concepts of machine learning in a practical sense providing complete code and implementation for real world examples in electrical, oil and gas, e-Commerce, and Hi-tech industry. The focus is on Python programming for machine learning and patterns involved in decision science for handling data. Features: Explains the basic concepts of Python and its role in machine learning. Provides comprehensive coverage of feature-engineering including real-time case studies. Perceives the structural patterns with reference to data science and statistics and analytics. Includes machine learning-based structured exercises. Appreciates different algorithmic concepts of machine learning including unsupervised, supervised, and reinforcement learning. This book is aimed at Researchers, Professionals, and Graduate Students in Data Science, Machine Learning, Computer Science, Electrical, and Computer Engineering"-- Provided by publisher
546			_aEng
650			_aPython (Computer program language) _93584
650			_aMachine learning
650			_aBig data
700	1		_aSumathi, S. _913439
700	1		_aRajappa, Suresh _913440
700	1		_aKumar, L. Ashok _913441
700	1		_aPaneerselvam, Surekha _913442
942			_cBK
999			_c141338 _d141338