Machine learning theory and practice / Jugal Kalita.
| Author/creator | Kalita, Jugal Kumar |
| Format | Electronic |
| Edition | First edition. |
| Publication Info | Boca Raton : Chapman & Hall/CRC Press, 2023. |
| Description | pages cm |
| Supplemental Content | Full text available from Taylor & Francis eBooks |
| Subjects |
| Abstract | "Machine Learning: Theory and Practice provides an introduction to the most popular methods in machine learning. The book covers regression including regularization, tree-based methods including Random Forests and Boosted Trees, Artificial Neural Networks including Convolutional Neural Networks (CNNs), reinforcement learning, and unsupervised learning focused on clustering. Topics are introduced in a conceptual manner along with necessary mathematical details. The explanations are lucid, illustrated with figures and examples. For each machine learning method discussed, the book presents appropriate libraries in the R programming language along with programming examples"-- 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 | 2022032123 |
| ISBN | 9780367433543 (hardback) |
| ISBN | 9780367433529 (paperback) |
| ISBN | (ebook) |