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      Training Data for Machine Learning

      2 in stock

      Firm sale: non returnable item
      SKU 9781492094524 Categories ,
      Select Guide Rating
      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 resou...

      £52.99

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      Description

      Product ID:9781492094524
      Product Form:Paperback / softback
      Country of Manufacture:GB
      Title:Training Data for Machine Learning
      Authors:Author: Anthony Sarkis
      Page Count:329
      Subjects:Machine learning, Machine learning
      Description:Select Guide Rating
      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
      Imprint Name:O'Reilly Media
      Publisher Name:O'Reilly Media
      Country of Publication:GB
      Publishing Date:2023-12-19

      Additional information

      Weight580 g
      Dimensions232 × 178 × 20 mm