Ultimate MLOps for Machine Learning Models: Use Real Case Studies to Efficiently Build, Deploy, and Scale Machine Learning Pipelines with MLOps
Author: Saurabh D. Dorle (Author)
Publisher finelybook 出版社: Orange Education Pvt. Ltd
Publication Date 出版日期: 2024-08-30
Language 语言: English
Print Length 页数: 314 pages
ISBN-10: 8197651205
ISBN-13: 9788197651205
Book Description
The only MLOps guide you’ll ever need
Book Description
This book is an essential resource for professionals aiming to streamline and optimize their machine learning operations. This comprehensive guide provides a thorough understanding of the MLOps life cycle, from model development and training to deployment and monitoring. By delving into the intricacies of each phase, the book equips readers with the knowledge and tools needed to create robust, scalable, and efficient machine learning workflows.
Key chapters include a deep dive into essential MLOps tools and technologies, effective data pipeline management, and advanced model optimization techniques. The book also addresses critical aspects such as scalability challenges, data and model governance, and security in machine learning operations. Each topic is presented with practical insights and real-world case studies, enabling readers to apply best practices in their job roles.
Table of Contents
1. Introduction to MLOps
2. Understanding Machine Learning Lifecycle
3. Essential Tools and Technologies in MLOps
4. Data Pipelines and Management in MLOps
5. Model Development and Training
6. Model Optimization Techniques for Performance
7. Efficient Model Deployment and Monitoring Strategies
8. Scalability Challenges and Solutions in MLOps
9. Data, Model Governance, and Compliance in Production Environments
10. Security in Machine Learning Operations
11. Case Studies and Future Trends in MLOps
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