Semi-supervised Learning (Adaptive Computation And Machine Learning)

Price: $103.98
(as of Dec 24,2024 05:28:54 UTC – Details)

Publisher ‏ : ‎ Mit Pr (January 1, 2006)
Language ‏ : ‎ English
Hardcover ‏ : ‎ 598 pages
ISBN-10 ‏ : ‎ 0262033585
ISBN-13 ‏ : ‎ 978-0262033589
Item Weight ‏ : ‎ 2.08 pounds
Dimensions ‏ : ‎ 8 x 1.25 x 10 inches

Semi-supervised Learning: A Powerful Approach in Machine Learning

Semi-supervised learning is a powerful approach in machine learning that leverages both labeled and unlabeled data to improve model performance. In the book “Semi-supervised Learning” by Olivier Chapelle, Bernhard Schölkopf, and Alexander Zien, the authors delve into the theory and practical applications of this cutting-edge technique.

With the exponential growth of data in today’s digital age, labeled data can be scarce and expensive to obtain. Semi-supervised learning offers a cost-effective solution by utilizing the vast amounts of unlabeled data that are readily available. By incorporating this additional information, models can generalize better and achieve higher accuracy.

The book explores various algorithms and methods used in semi-supervised learning, such as self-training, co-training, and graph-based methods. It also discusses the challenges and limitations of the approach, along with strategies to overcome them.

Whether you are a seasoned machine learning practitioner or just starting out, “Semi-supervised Learning” provides valuable insights and techniques to enhance your understanding and application of this innovative approach. Dive into the world of semi-supervised learning and unlock its full potential in adaptive computation and machine learning.
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