Practical MLOps Operationalizing Machine Learning Models(1st Edition)
Authors:
Noah Gift , Alfredo Deza
In Stock: 1 Left
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Solution Manual Includes
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$9.99
Book details
ISBN: 1098103017, 978-1098103019
Book publisher: O'Reilly Media
Book Price $0 : In 'Practical MLOps: Operationalizing Machine Learning Models', authors Noah Gift and Alfredo Deza offer a comprehensive guide to deploying machine learning (ML) models in production. This book is a solution manual for data scientists and engineers transitioning from model training to creating scalable, reliable pipelines that can handle real-world data. The book thoroughly explores the MLOps lifecycle, emphasizing automating workflows and collaborating between data science and operational teams. Open-source tools like Docker, Kubernetes, and TensorFlow are discussed at length, providing the answer key to overcoming common deployment challenges. Furthermore, the table of contents includes sections on continuous integration and delivery (CI/CD) for ML, data management, and model monitoring—key areas often neglected in the journey from development to production. Through practical examples and case studies, the authors illustrate the importance of aligning technical skills with organizational goals in order to implement effective ML solutions efficiently and robustly. Reception of the book highlights its in-depth content and applicability in professional settings, making it an essential resource for practitioners aiming to scale machine learning initiatives successfully. Students will benefit from the cheap accessibility of this guide, ideal for supplementary study.
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