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The Machine Learning Solutions Architect Handbook

You're reading from   The Machine Learning Solutions Architect Handbook Practical strategies and best practices on the ML lifecycle, system design, MLOps, and generative AI

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Product type Paperback
Published in Apr 2024
Publisher Packt
ISBN-13 9781805122500
Length 602 pages
Edition 2nd Edition
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Author (1):
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David Ping David Ping
Author Profile Icon David Ping
David Ping
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Toc

Table of Contents (19) Chapters Close

Preface 1. Navigating the ML Lifecycle with ML Solutions Architecture FREE CHAPTER 2. Exploring ML Business Use Cases 3. Exploring ML Algorithms 4. Data Management for ML 5. Exploring Open-Source ML Libraries 6. Kubernetes Container Orchestration Infrastructure Management 7. Open-Source ML Platforms 8. Building a Data Science Environment Using AWS ML Services 9. Designing an Enterprise ML Architecture with AWS ML Services 10. Advanced ML Engineering 11. Building ML Solutions with AWS AI Services 12. AI Risk Management 13. Bias, Explainability, Privacy, and Adversarial Attacks 14. Charting the Course of Your ML Journey 15. Navigating the Generative AI Project Lifecycle 16. Designing Generative AI Platforms and Solutions 17. Other Books You May Enjoy
18. Index

Data storage and management

ML workloads often require data from diverse sources and in various formats, and the sheer volume of data can be substantial, particularly when dealing with unstructured data. To address these requirements, cloud object data storage solutions like Amazon S3 are commonly employed as the underlying storage medium. Conceptually, cloud object storage can be likened to a file storage system that accommodates files of different formats. Moreover, the storage system allows for the organization of files using prefixes, which serve as virtual folders for enhanced object management. It is important to note that these prefixes do not correspond to physical folder structures. The term "object storage" stems from the fact that each file is treated as an independent object, bundled with metadata and assigned a unique identifier. Object storage boasts features such as virtually unlimited storage capacity, robust object analytics based on metadata, API-based access...

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