Machine learning for decision sciences with case studies in Python / S. Sumathi, Suresh Rajappa, L. Ashok Kumar, Surekha Paneerselvam.
| Author/creator | Sumathi, S., 1968- |
| Other author | Rajappa, Suresh. |
| Other author | Kumar, L. Ashok. |
| Other author | Surekha, P., 1980- |
| Format | Electronic |
| Edition | First edition. |
| Publication Info | Boca Raton : CRC Press, 2022. |
| Description | pages cm |
| Supplemental Content | Full text available from Taylor & Francis eBooks |
| Subjects |
| Abstract | "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. |
| Bibliography note | Includes bibliographical references and index. |
| Access restriction | Available only to authorized users. |
| Technical details | Mode of access: World Wide Web |
| Genre/form | Electronic books. |
| LCCN | 2021058604 |
| ISBN | 9781032193564 (hardback) |
| ISBN | 9781032193571 (paperback) |
| ISBN | (ebook) |