Jindong Wang
Introduction to Transfer Learning: Algorithms and Practice - Machine Learning: Foundations, Methodologies, and Applications Jindong Wang 2023 edition

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Introduction to Transfer Learning: Algorithms and Practice - Machine Learning: Foundations, Methodologies, and Applications

Jindong Wang

2023 edition

Transfer learning is one of the most important technologies in the era of artificial intelligence and deep learning. It seeks to leverage existing knowledge by transferring it to another, new domain. Over the years, a number of relevant topics have attracted the interest of the research and application community: transfer learning, pre-training and fine-tuning, domain adaptation, domain generalization, and meta-learning.

This book offers a comprehensive tutorial on an overview of transfer learning, introducing new researchers in this area to both classic and more recent algorithms. Most importantly, it takes a "student's" perspective to introduce all the concepts, theories, algorithms, and applications, allowing readers to quickly and easily enter this area. Accompanying the book, detailed code implementations are provided to better illustrate the core ideas of several important algorithms, presenting good examples for practice.

409 pages, 40 Tables, color; 84 Illustrations, color; 25 Illustrations, black and white; X, 409 p. 1

Medij	Knjige Hardcover Book (Knjiga s trdim hrbtom in platnicami)
Izdano	31. marca 2023
ISBN13	9789811975837
Založniki	Springer Verlag, Singapore
Strani	329
Dimenzije	242 × 161 × 27 mm · 668 g
Jezik	Angleščina