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

Product type Paperback

Published in Jan 2022

Publisher Packt

ISBN-13 9781801072168

Length 442 pages

Edition 1st Edition

Languages

Python

Tools

TensorFlow

Concepts

Machine Learning

Author (1):

David Ping

View More author details

Table of Contents (17) Chapters

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 media and entertainment

The media and entertainment (M&E) industry consists of businesses that engage in the production and distribution of films, television, streaming content, music, games, and publishing. The current M&E landscape has been shaped by the increasing adoption of streaming and over-the-top (OTT) content delivery versus traditional broadcasting. M&E customers, faced with ever-increasing media content choices, are shifting their consumption habits and demanding more personalized and enhanced experiences across different devices, anytime, anywhere. M&E companies are also faced with fierce competition in the industry, and to stay competitive, M&E companies need to identify new monetization channels, improve user experience, and improve operational efficiency. The following diagram shows the main steps in the media production and distribution workflow:

Figure 2.10 – Media production and distribution workflow...