Applied machine learning / M. Gopal.
| Author/creator | Gopal, M. |
| Format | Electronic |
| Publication Info | New York : McGraw-Hill Education, [2019] |
| Description | XIX, 630 pages ; illustrations ; 27 cm |
| Supplemental Content | Full text available from AccessEngineering |
| Subjects |
| Contents | Introduction -- Supervised learning: rationale and basics -- Statistical learning -- Learning with Support Vector Machines (SVM) -- Learning with Neural Networks (NN) -- Fuzzy inference systems -- Data clustering and data transformations -- Decision tree learning -- Business intelligence and data mining : techniques and applications -- Appendix A: Genetic Algorithm (GA) for search optimization -- Appendix B: Reinforcement Learning (RL) -- Datasets from real-life applications for machine learning experiments -- Problems. |
| Abstract | "This comprehensive textbook explores the theoretical underpinnings of learning and equips readers with the knowledge needed to apply powerful machine learning techniques to solve challenging real-world problems. Applied Machine Learning shows, step by step, how to conceptualize problems, acurately represent data, select and tune algorithms, interpret and analyze results, and make informed strategic decisions. Presented in a non-rigorous mathematical syle, the book covers a broad array of machine learning ropics with special emphasis on methods that have been profitably employed." -- back cover. |
| Bibliography note | Includes bibliographical references (pages 613-622) and index. |
| Access restriction | Available only to authorized users. |
| Technical details | Mode of access: World Wide Web |
| Genre/form | Electronic books. |
| LCCN | 2018966932 |
| ISBN | 9781260456844 (hardcover) |
| ISBN | 1260456846 (hardcover) |
Availability
| Library | Location | Call Number | Status | Item Actions |
|---|---|---|---|---|
| Electronic Resources | Access Content Online | ✔ Available |