Description: Algorithms and Practice : Algorithms and Practice, Hardcover by Wang, Jindong; Chen, Yiqiang, ISBN 9811975833, ISBN-13 9789811975837, Brand New, Free shipping in the US 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 th, detailed code implementations are provided to better illustrate the core ideas of several important algorithms, presenting good examples for practice.
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Book Title: Algorithms and Practice : Algorithms and Practice
Number of Pages: Xxi, 329 Pages
Publication Name: Introduction to Transfer Learning : Algorithms and Practice
Language: English
Publisher: Springer
Publication Year: 2023
Subject: Computer Graphics, Probability & Statistics / General, Intelligence (Ai) & Semantics, Computer Science, Speech & Audio Processing
Type: Textbook
Item Weight: 24.5 Oz
Subject Area: Mathematics, Computers
Item Length: 9.3 in
Author: Jindong Wang, Yiqiang Chen
Series: Machine Learning: Foundations, Methodologies, and Applications Ser.
Item Width: 6.1 in
Format: Hardcover
