Introduction to Transfer Learning is popular PDF and ePub book, written by Jindong Wang in 2023-03-30, it is a fantastic choice for those who relish reading online the Computers genre. Let's immerse ourselves in this engaging Computers book by exploring the summary and details provided below. Remember, Introduction to Transfer Learning can be Read Online from any device for your convenience.
Introduction to Transfer Learning Book PDF Summary
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.
Detail Book of Introduction to Transfer Learning PDF
- Author : Jindong Wang
- Release : 30 March 2023
- Publisher : Springer Nature
- ISBN : 9789811975844
- Genre : Computers
- Total Page : 333 pages
- Language : English
- PDF File Size : 17,8 Mb
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