An edition of Machine Learning in Production
(2025)
Machine Learning in Production
From Models to Products
by Christian Kastner
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| Edition | Availability |
|---|---|
1
Machine Learning in Production: From Models to Products
Apr 08, 2025, The MIT Press
hardcover
in English
0262049724 9780262049726
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Book Details
First Sentence
"Machine learning (ML) has enabled incredible advances in the capabilities of software products, allowing us to design systems that would have seemed like science fiction only one or two decades ago, such as personal assistants answering voice prompts, medical diagnoses outperforming specialists, autonomous delivery drones, and tools creatively manipulating photos and video with natural language instructions."
Table of Contents
Cover
Setting the Stage
1. Introduction
2. From Models to Systems
3. Machine Learning for Software Engineers, in a Nutshell
Requirements Engineering
4. When to use Machine Learning
5. Setting and Measuring Goals
6. Gathering Requirements
7. Planning for Mistakes
Architecture and Design
8. Thinking like a Software Architect
9. Quality Attributes of ML Components
10. Deploying a Model
11. Automating the Pipeline
12. Scaling the System
13. Planning for Operations
Quality Assurance
14. Quality Assurance Basics
15. Model Quality
16. Data Quality
17. Pipeline Quality
18. System Quality
19. Testing and Experimenting in Production
Process and Teams
20. Data Science and Software Engineering Process Models
21. Interdisciplinary Teams
22. Technical Debt
Responsible ML Engineering
23. Responsible Engineering
24. Versioning, Provenance, and Reproducibility
25. Explainability
26. Fairness
27. Safety
28. Security and Privacy
29. Transparency and Accountability
Edition Notes
Source title: Machine Learning in Production: From Models to Products
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| July 23, 2025 | Created by emggeorge | import new book |