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The Machine Learning Solutions Architect Handbook

You're reading from   The Machine Learning Solutions Architect Handbook Create machine learning platforms to run solutions in an enterprise setting

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Product type Paperback
Published in Jan 2022
Publisher Packt
ISBN-13 9781801072168
Length 442 pages
Edition 1st Edition
Languages
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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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Table of Contents (17) Chapters Close

Preface 1. Section 1: Solving Business Challenges with Machine Learning Solution Architecture
2. Chapter 1: Machine Learning and Machine Learning Solutions Architecture FREE CHAPTER 3. Chapter 2: Business Use Cases for Machine Learning 4. Section 2: The Science, Tools, and Infrastructure Platform for Machine Learning
5. Chapter 3: Machine Learning Algorithms 6. Chapter 4: Data Management for Machine Learning 7. Chapter 5: Open Source Machine Learning Libraries 8. Chapter 6: Kubernetes Container Orchestration Infrastructure Management 9. Section 3: Technical Architecture Design and Regulatory Considerations for Enterprise ML Platforms
10. Chapter 7: Open Source Machine Learning Platforms 11. Chapter 8: Building a Data Science Environment Using AWS ML Services 12. Chapter 9: Building an Enterprise ML Architecture with AWS ML Services 13. Chapter 10: Advanced ML Engineering 14. Chapter 11: ML Governance, Bias, Explainability, and Privacy 15. Chapter 12: Building ML Solutions with AWS AI Services 16. Other Books You May Enjoy

ML use cases in manufacturing

Manufacturing is an industry sector that produces tangible finished products. It includes many sub-sectors such as consumer goods, electronics goods, industrial equipment, automobiles, furniture, building materials, sporting goods, clothing, and toys. There are multiple stages in a typical product manufacturing life cycle, including product design, prototyping, manufacturing and assembling, and post-manufacturing service and support. The following diagram shows the typical business functions and flow in the manufacturing sector:

Figure 2.16 – Manufacturing business process flow

AI and ML have played an essential role in the manufacturing process, such as sales forecasting, predictive machine maintenance, quality control and robotic automation for manufacturing quality and yield, and process and supply chain optimization to improve overall operational efficiency.

Engineering and product design

Product design is the...

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