• Read online: Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps

    Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps. Valliappa Lakshmanan, Sara Robinson, Michael Munn

     

    Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps

     


    Machine-Learning-Design.pdf
    ISBN: 9781098115784 | 400 pages | 10 Mb
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    • Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps
    • Valliappa Lakshmanan, Sara Robinson, Michael Munn
    • Page: 400
    • Format: pdf, ePub, fb2, mobi
    • ISBN: 9781098115784
    • Publisher: O'Reilly Media, Incorporated

    Download Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps

     

     

    Books pdf download Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps in English 9781098115784

     

    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 models Represent data for different ML model types, including embeddings, feature crosses, and more Choose the right model type for specific problems Build a robust training loop that uses checkpoints, distribution strategy, and hyperparameter tuning Deploy scalable ML systems that you can retrain and update to reflect new data Interpret model predictions for stakeholders and ensure that models are treating users fairly

    AIDevFest20: Machine Learning Design Patterns for MLOps
    For data scientists and ML engineers, these patterns provide a way to apply hard-won Anyone designing Machine Learning Design Patterns (part 1): author talk | Meetup
    This book provides clear solutions to common challenges in data preparation, model building and MLOps. Wouldn't it be great if we can make learning a bit more  Michael Munn - Mathematical Analysis - Amazon.com
    Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps. by Valliappa Lakshmanan , Sara  ONLINE EROFLUEDEN// Machine Learning - SlideShare
    ONLINE EROFLUEDEN// Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps. Machine Learning Design Patterns: Solutions to Common
    Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and Mlops (Paperback). Machine 



     

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