Human-in-the-Loop Machine Learning: Active learning and annotation for human-centered AI

Price: $59.99 – $49.54
(as of Dec 18,2024 08:06:48 UTC – Details)

Publisher ‏ : ‎ Manning (July 20, 2021)
Language ‏ : ‎ English
Paperback ‏ : ‎ 424 pages
ISBN-10 ‏ : ‎ 1617296740
ISBN-13 ‏ : ‎ 978-1617296741
Item Weight ‏ : ‎ 1.58 pounds
Dimensions ‏ : ‎ 7.38 x 1 x 9.25 inches

Human-in-the-Loop Machine Learning: Active learning and annotation for human-centered AI

In the ever-evolving field of artificial intelligence, human-in-the-loop machine learning is gaining traction as a powerful tool for creating more human-centered AI systems. By incorporating human feedback and expertise into the machine learning process, these systems can be more transparent, trustworthy, and aligned with human values.

One key aspect of human-in-the-loop machine learning is active learning, where the machine learning model actively selects the most informative data points for human annotation. This helps to reduce the amount of labeled data needed for training, making the process more efficient and cost-effective. By focusing on the most relevant data, active learning can also improve the accuracy and generalizability of AI models.

Another important component of human-in-the-loop machine learning is annotation, where humans provide labels or annotations to guide the machine learning process. This can involve tasks such as categorizing images, transcribing text, or labeling objects in videos. By involving humans in the annotation process, AI systems can learn from human expertise and better understand complex, nuanced concepts.

Overall, human-in-the-loop machine learning holds great promise for creating AI systems that are more responsive to human needs and preferences. By incorporating active learning and annotation, these systems can benefit from the best of both human and machine intelligence, leading to more robust and effective AI solutions.
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