Human-in-the-Loop Machine Learning active learning and annotation for human - centered AI
Material type:
TextPublication details: New York Manning pub. 2021Description: 398 pISBN: 9781617296741Subject(s): Artifitial intelligence | machin learningDDC classification: 006.3 Summary: Most machine learning systems that are deployed in the world today learn from human feedback. However, most machine learning courses focus almost exclusively on the algorithms, not the human-computer interaction part of the systems. This can leave a big knowledge gap for data scientists working in real-world machine learning, where data scientists spend more time on data management than on building algorithms. Human-in-the-Loop Machine Learning is a practical guide to optimizing the entire machine learning process, including techniques for annotation, active learning, transfer learning, and using machine learning to optimize every step of the process.
| Item type | Current library | Collection | Call number | Status | Date due | Barcode |
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BK
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Kannur University Central Library Stack | Stack | 006.3 MON/H (Browse shelf (Opens below)) | Available | 68208 |
Most machine learning systems that are deployed in the world today learn from human feedback. However, most machine learning courses focus almost exclusively on the algorithms, not the human-computer interaction part of the systems. This can leave a big knowledge gap for data scientists working in real-world machine learning, where data scientists spend more time on data management than on building algorithms. Human-in-the-Loop Machine Learning is a practical guide to optimizing the entire machine learning process, including techniques for annotation, active learning, transfer learning, and using machine learning to optimize every step of the process.
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