000			02936nam a22003017a 4500
003			ZW-GwMSU
005			20211201135524.0
008			211201b |||||||| |||| 00| 0 eng d
020			_a9780128147610 _q(paperback)
040			_arda _beng _erda _cMSU
050	0	0	_aQA76.9.D343 _bKOT
100	1		_aKotu, Vijay, _eauthor.
245	1	0	_aData science : _bconcepts and practice / _ccreated by Vijay Kotu and Bala Deshpande.
250			_aSecond edition.
264		1	_aCambridge, MA : _bElsevier/Morgan Kaufmann Publishers, _c2019 _cc2019
300			_axix, 548 pages : _billustrations ; _c24 cm
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
504			_aIncludes bibliographical references and index.
520			_aLearn the basics of Data Science through an easy to understand conceptual framework and immediately practice using Rapid Miner platform. Whether you are brand new to data science or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Science has become an essential tool to extract value from data for any organization that collects, stores and processes data as part of its operations. This book is ideal for business users, data analysts, business analysts, engineers, and analytics professionals and for anyone who works with data. You'll be able to: Gain the necessary knowledge of different data science techniques to extract value from data. Master the concepts and inner workings of 30 commonly used powerful data science algorithms. Implement step-by-step data science process using using Rapid Miner, an open source GUI based data science platform Data Science techniques covered: Exploratory data analysis, Visualization, Decision trees, Rule induction, k-nearest neighbors, Naïve Bayesian classifiers, Artificial neural networks, Deep learning, Support vector machines, Ensemble models, Random forests, Regression, Recommendation engines, Association analysis, K-Means and Density based clustering, Self organizing maps, Text mining, Time series forecasting, Anomaly detection, Feature selection and more...Contains fully updated content on data science, including tactics on how to mine business data for information Presents simple explanations for over twenty powerful data science techniques Enables the practical use of data science algorithms without the need for programming Demonstrates processes with practical use cases Introduces each algorithm or technique and explains the workings of a data science algorithm in plain language Describes the commonly used setup options for the open source tool Rapid Miner
650		0	_aData mining.
650		0	_aConsumer behavior.
650		0	_aElectronic data processing.
650		0	_aBusiness _xData processing
700			_aDeshpande Bala _eauthor
942			_2lcc _cB
999			_c158184 _d158184