| 书目名称 | Introduction to Transfer Learning | | 副标题 | Algorithms and Pract | | 编辑 | Jindong Wang,Yiqiang Chen | | 视频video | | | 概述 | Fast and painless icebreaker for your journey into transfer learning.Clear summaries of both classic and more recent algorithms.Complementary source codes for good practice examples | | 丛书名称 | Machine Learning: Foundations, Methodologies, and Applications | | 图书封面 |  | | 描述 | .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.. | | 出版日期 | Book 2023 | | 关键词 | Transfer learning; Domain adaption; Domain generalization; Meta-learning; Transfer of learning; Knowledge | | 版次 | 1 | | doi | https://doi.org/10.1007/978-981-19-7584-4 | | isbn_softcover | 978-981-19-7586-8 | | isbn_ebook | 978-981-19-7584-4Series ISSN 2730-9908 Series E-ISSN 2730-9916 | | issn_series | 2730-9908 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor |
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发表于 2025-3-21 16:46:27
