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Machine Learning Design Patterns

Machine Learning Design Patterns

Valliappa Lakshmanan
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The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog proven methods to help data scientists tackle common problems throughout the ML process. These design patterns codify the experience of hundreds of experts into straightforward, approachable advice.

In this book, you will find detailed explanations of 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 best technique for your situation.

You'll learn how to:

  • Identify and mitigate common challenges when training, evaluating, and deploying ML models
  • Represent data for different ML model types, including embeddings, feature crosses, and more
  • Choose the right model type for specific...
  • Année:
    2020
    Editeur::
    O'Reilly Media
    Langue:
    english
    ISBN 10:
    1098115783
    ISBN 13:
    9781098115784
    Fichier:
    EPUB, 17.56 MB
    IPFS:
    CID , CID Blake2b
    english, 2020
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