Machine Learning

丛 书 名：Machine Learning: Foundations, Methodologies, and Applications

版本说明：1

作     者：Alexander Jung 

I S B N：(纸本) 9789811681929;9789811681950 

出 版 社：Springer Singapore 

出 版 年：1000年

页      数：XVII, 212页

主 题 词：Machine Learning Data Structures and Information Theory Artificial Intelligence Theory of Computation Data Mining and Knowledge Discovery 

摘      要：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 tospecific design choices for the model, data, and loss of a ML method.