Machine learning for decision sciences with case studies in Python
Author(s)
Bibliographic Information
Machine learning for decision sciences with case studies in Python
CRC Press, 2022
- : hbk
Available at / 2 libraries
-
No Libraries matched.
- Remove all filters.
Note
Other authors: Suresh Rajappa, L. Ashok Kumar, Surekha Paneerselvam
Includes bibliographical references (p. 449-451) and index
Description and Table of Contents
Description
Explains the basic concepts of Python and its role in machine learning
Provides comprehensive coverage of feature-engineering including real-time case studies
Perceive 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
Table of Contents
1. Introduction 2. Overview of Python for Machine Learning 3. Data Analytics Life Cycle for Machine Learning 4. Unsupervised Learning 5. Supervised Learning: Regression 6. Supervised Learning: Classification 7. Feature Engineering 8. Reinforcement Learning 9. Case Studies for Decision Sciences Using Python
by "Nielsen BookData"
