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.pdf
ISBN: 9781098115784 | 400 pages | 10 Mb

- 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
Free best selling ebook downloads Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps by Valliappa Lakshmanan, Sara Robinson, Michael Munn English version 9781098115784
Machine Learning Design Patterns Tickets, Wed, Nov 18 Design patterns capture best practices and solutions to recurring problems. Join us for the great talks and AMA, by the authors of the newly
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.
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 - Enterprise Applications - Amazon.com Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps. by Valliappa Lakshmanan , Sara
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.
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.
Machine Learning Design Patterns: Solutions to Common 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.
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