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(Get Now) Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps *ePub
(Get Now) Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps *ePub
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The design patterns in this book capture best practices and solutions to recurring problems in machine learning. Authors Valliappa Lakshmanan, Sara Robinson, and Michael Munn catalog the first tried-and-proven methods to help engineers tackle problems that frequently crop up during the ML process. These design patterns codify the experience of hundreds of experts into advice you can easily follow.The authors, three Google Cloud engineers, describe 30 patterns for data and problem representation, operationalization, repeatability, reproducibility, flexibility, explainability, and fairness. Each pattern includes a description of the problem, a variety of potential solutions, and recommendations for choosing the most appropriate remedy for your situation.You?ll learn how to:Identify and mitigate common challenges when training, evaluating, and deploying ML modelsRepresent data for different ML model types, including embeddings, feature crosses, and moreChoose the right model type for
Author : Valliappa Lakshmanan
Pages : 400 pages
Publisher : O'Reilly Media
Language : eng
ISBN-10 : 1098115783
ISBN-13 : 9781098115784
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