Introduction to Transfer Learning: Algorithms and Practice - Paperback
4.5 (1,234)
Sold 100+ last 30 days
20% off first order
$89.08
Color
Black
Quantity
Product description loading
Product description loading
This is the product description text that will appear here.
Quantity
1
Comprehensive tutorial on transfer learning: Guides readers through both classic and recent algorithms for a thorough understanding
Detailed code implementations: Provides practical examples to illustrate core concepts and algorithms
Student-focused approach: Simplifies complex ideas for quick and easy entry into the field
Covers multiple research areas: Explores pre-training, fine-tuning, domain adaptation, domain generalization, and meta learning
Up-to-date with current research: Includes insights relevant to the latest advancements in transfer learning
Summarized by Shop
Report copyright infringement by Jindong Wang (Author), Yiqiang Chen (Author)
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 i