Machine Learning - the Basics
| Author/creator | Jung, Alexander Author |
| Format | Electronic |
| Publication Info | New York : Springer Berlin : Springer [Distributor] |
| Description | xvii, 212 p. ill 23.500 x 015.500 cm. |
| Supplemental Content | Full text available from Springer Nature - Springer Computer Science eBooks 2022 English International |
| Supplemental Content | Full text available from Springer Books |
| Subjects |
| Series | Machine Learning: Foundations, Methodologies, and Applications Ser. |
| Summary | Annotation Machine learning (ML) has become a commonplace element in our everyday lives and a standard tool for many fields of science and engineering. To make optimal use of ML, it is essential to understand its underlying principles. <br>This book approaches ML as the computational implementation of the scientific principle. This principle consists of continuously adapting a model of a given data-generating phenomenon by minimizing some form of loss incurred by its predictions. <br>The book trains readers to break down various ML applications and methods in terms of data, model, and loss, thus helping them to choose from the vast range of ready-made ML methods.<br>The book's three-component approach to ML provides uniform coverage of a wide range of concepts and techniques. As a case in point, techniques for regularization, privacy-preservation as well as explainability amount to specific design choices for the model, data, and loss of a ML method. <br> |
| Access restriction | Available only to authorized users. |
| Technical details | Mode of access: World Wide Web |
| Genre/form | Electronic books. |
| ISBN | 9789811681929 |
| ISBN | 9811681929 (Trade Cloth) Active Record |
| Standard identifier# | 9789811681929 |
| Stock number | 978-981-16-8192-9 00024965 |
Availability
| Library | Location | Call Number | Status | Item Actions |
|---|---|---|---|---|
| Electronic Resources | Access Content Online | ✔ Available |