Jindong Wang,Yiqiang Chen
Introduction to Transfer Learning: Algorithms and Practice
Introduction to Transfer Learning: Algorithms and Practice
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Transfer learning is a crucial technology in AI and deep learning, leveraging existing knowledge to transfer it to new domains. This book provides a comprehensive tutorial on transfer learning, introducing classic and recent algorithms, and accompanying code implementations for better illustration.
Format: Hardback
Length: 329 pages
Publication date: 31 March 2023
Publisher: Springer Verlag, Singapore
Transfer learning is a crucial technology in the realm of artificial intelligence and deep learning, playing a pivotal role in leveraging existing knowledge to adapt to new domains. Over the years, various relevant topics within this field have garnered significant attention from the research and application communities, including transfer learning, pre-training and fine-tuning, domain adaptation, domain generalization, and meta-learning.
In this comprehensive tutorial, aimed at introducing new researchers to the world of transfer learning, we delve into both classic and more recent algorithms. We adopt a student-centric approach, presenting all the concepts, theories, algorithms, and applications in a clear and concise manner, ensuring a smooth entry into this exciting area.
To enhance understanding, we provide detailed code implementations alongside the book, showcasing the core ideas of several important algorithms through practical examples. These code implementations serve as valuable resources for readers, allowing them to apply and refine their knowledge in real-world scenarios.
By exploring the diverse aspects of transfer learning, this book equips readers with the skills and knowledge necessary to apply this powerful technology to a wide range of applications, from image recognition to natural language processing and beyond. Whether you are a novice or an experienced practitioner, this book will be your invaluable guide to unlocking the full potential of transfer learning in the era of artificial intelligence.
Weight: 668g
Dimension: 161 x 242 x 27 (mm)
ISBN-13: 9789811975837
Edition number: 1st ed. 2023
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