Data Science : Concepts and Practice
Language: English
Published by Elsevier Inc, 2018
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
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Add to basketItem description from seller
nach der Bestellung gedruckt Neuware - Printed after ordering - Learn the basics of Data Science through an easy to understand conceptual framework and immediately practice using RapidMiner 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 RapidMiner, 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.…
Seller Inventory # 9780128147610
- Title
- Data Science : Concepts and Practice
- Author
- Bala Deshpande
- Publisher
- Elsevier Inc
- Publication year
- 2018
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 012814761X
- ISBN 13
- 9780128147610
- Edition
- 2nd Edition
- Item weight
- 1,148 grams
- Dimensions
- 236x189x32 mm
Learn the basics of Data Science through an easy to understand conceptual framework and immediately practice using RapidMiner 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 RapidMiner, 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...
"Synopsis" may belong to another edition of this title.
About the Author
Dr. Deshpande has extensive experience in working with companies ranging from startups to Fortune 5 in fields ranging from automotive, aerospace, retail, food, and manufacturing verticals delivering business analysis; designing and developing custom data products for implementing business intelligence, data science, and predictive analytics solutions. He was the Founder of SimaFore, a predictive analytics consulting company which was acquired by Soliton Inc., a provider of testing solutions for the semiconductor industry. He was also the Founding Co-chair of the annual Predictive Analytics World-Manufacturing conference. In his professional career he has worked with Ford Motor Company on their product development, with IBM at their IBM Watson Center of Competence, and with Domino’s Pizza at their data science and artificial intelligence groups. He has a Ph.D. from Carnegie Mellon and an MBA from Ross School of Business, Michigan.
"About the title" may belong to another edition of this title.
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