A01=Anthony Sarkis
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AI artificial intelligence deep learning training data machine learning model drift production deep learning deep learning at scale supervised learning model supervision model bias
Author_Anthony Sarkis
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Category1=Non-Fiction
Category=UYQM
COP=United States
Delivery_Pre-order
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eq_nobargain
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Language_English
PA=Not yet available
Price_€50 to €100
PS=Forthcoming
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Product details
- ISBN 9781492094524
- Weight: 530g
- Dimensions: 178 x 232mm
- Publication Date: 19 Dec 2023
- Publisher: O'Reilly Media
- Publication City/Country: US
- Product Form: Paperback
- Language: English
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Your training data has as much to do with the success of your data project as the algorithms themselves--most failures in deep learning systems relate to training data. But while training data is the foundation for successful machine learning, there are few comprehensive resources to help you ace the process. This hands-on guide explains how to work with and scale training data. Data science professionals and machine learning engineers will gain a solid understanding of the concepts, tools, and processes needed to:
- Design, deploy, and ship training data for production-grade deep learning applications
- Integrate with a growing ecosystem of tools
- Recognize and correct new training data-based failure modes
- Improve existing system performance and avoid development risks
- Confidently use automation and acceleration approaches to more effectively create training data
- Avoid data loss by structuring metadata around created datasets
- Clearly explain training data concepts to subject matter experts and other shareholders
- Successfully maintain, operate, and improve your system
