February 2024
Intermediate to advanced
200 pages
11h 56m
English
Content preview from Machine Learning with Noisy LabelsBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Bibliography
Bibliography
- Adamopoulou and Moussiades, 2020 E. Adamopoulou, L. Moussiades, Chatbots: History, technology, and applications, Machine Learning with Applications 2020;2, 100006.
- Alayrac et al., 2019 J.B. Alayrac, J. Uesato, P.S. Huang, A. Fawzi, R. Stanforth, P. Kohli, Are labels required for improving adversarial robustness? Advances in Neural Information Processing Systems 2019;32.
- Albert et al., 2022 P. Albert, D. Ortego, E. Arazo, N.E. O'Connor, K. McGuinness, Addressing out-of-distribution label noise in webly-labelled data, Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. 2022:392–401.
- Algan and Ulusoy, 2021 G. Algan, I. Ulusoy, Image classification with deep learning in the presence of noisy labels: ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.