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 for download in pdf format Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps by Valliappa Lakshmanan, Sara Robinson, Michael Munn

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

Amazon.co.jp：カスタマーレビュー: Machine Learning
Amazon.com で、Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and Mlops の役立つカスタマー  Data Science Design Patterns: Morley, Todd: 9780134000053
Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps · Valliappa LakshmananValliappa  Machine Learning Design Patterns [Book] - O'Reilly
The design patterns in this book capture best practices and solutions to recurring to help data scientists tackle common problems throughout the ML process. Building Machine Learning Pipelines - Amazon.com
Building Machine Learning Pipelines: Automating Model Life Cycles with TensorFlow 1st Edition, Kindle Edition. by Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps. Online: ML Design Patterns and Designing ML Infrastructure
Designing, building, deploying, and scaling ML systems can be challenging. By utilizing design patterns, Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps 1st Edition. Machine Learning Design Patterns by Lakshmanan, Valliappa
Machine Learning Design Patterns Solutions to Common Challenges in Data Preparation, Model Building, and MLOps. Lakshmanan, Valliappa. Heftet / 2020 /  Machine Learning Design Patterns: Solutions to - Amazon.com
Amazon.com: Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps eBook: Lakshmanan,  Machine Learning Design Patterns by Google AI | Meetup
book “Machine Learning Design Patterns”, covering solutions to common challenges in Data Preparation, Model Building, and MLOps.



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