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The Machine Learning Solutions Architect Handbook - Second Edition

You're reading from  The Machine Learning Solutions Architect Handbook - Second Edition

Product type Book
Published in Apr 2024
Publisher Packt
ISBN-13 9781805122500
Pages 602 pages
Edition 2nd Edition
Languages
Author (1):
David Ping David Ping
Profile icon David Ping

Table of Contents (19) Chapters

Preface Navigating the ML Lifecycle with ML Solutions Architecture Exploring ML Business Use Cases Exploring ML Algorithms Data Management for ML Exploring Open-Source ML Libraries Kubernetes Container Orchestration Infrastructure Management Open-Source ML Platforms Building a Data Science Environment Using AWS ML Services Designing an Enterprise ML Architecture with AWS ML Services Advanced ML Engineering Building ML Solutions with AWS AI Services AI Risk Management Bias, Explainability, Privacy, and Adversarial Attacks Charting the Course of Your ML Journey Navigating the Generative AI Project Lifecycle Designing Generative AI Platforms and Solutions Other Books You May Enjoy
Index

Testing your knowledge

Great job! You have reached to the end of the chapter. Now, let's put your newly acquired knowledge to the test and see if you've understood and retained the information presented.Take a look at the list of the following scenarios and determine which of the three ML types can be applied (supervised, unsupervised, or reinforcement):

  1. There is a list of online feedback on products. Each comment has been labeled with a sentiment class (for example, positive, negative, neutral). You have been asked to build an ML model to predict the sentiment of new feedback.
  2. You have historical house pricing information and details about the house, such as zip code, number of bedrooms, house size, and house condition. You have been asked to build an ML model to predict the price of a house.
  3. You have been asked to identify potentially fraudulent transactions on your company's e-commerce site. You have data such as historical transaction data, user information, credit...
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