Description
| Product ID: | 9789811681929 |
| Product Form: | Hardback |
| Country of Manufacture: | GB |
| Series: | Machine Learning: Foundations, Methodologies, and Applications |
| Title: | Machine Learning |
| Subtitle: | The Basics |
| Authors: | Author: Alexander Jung |
| Page Count: | 212 |
| Subjects: | Databases, Databases, Data mining, Mathematical theory of computation, Artificial intelligence, Expert systems / knowledge-based systems, Machine learning, Data mining, Mathematical theory of computation, Artificial intelligence, Expert systems / knowledge-based systems, Machine learning |
| Description: | Select Guide Rating 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. The book’s three-component approach to ML provides uniform coverage of a wide range of concepts and techniques. 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. 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. 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. 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. |
| Imprint Name: | Springer Verlag, Singapore |
| Publisher Name: | Springer Verlag, Singapore |
| Country of Publication: | GB |
| Publishing Date: | 2022-01-22 |
