Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Active Machine Learning with Python

You're reading from   Active Machine Learning with Python Refine and elevate data quality over quantity with active learning

Arrow left icon
Product type Paperback
Published in Mar 2024
Publisher Packt
ISBN-13 9781835464946
Length 176 pages
Edition 1st Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
Margaux Masson-Forsythe Margaux Masson-Forsythe
Author Profile Icon Margaux Masson-Forsythe
Margaux Masson-Forsythe
Arrow right icon
View More author details
Toc

Table of Contents (13) Chapters Close

Preface 1. Part 1: Fundamentals of Active Machine Learning
2. Chapter 1: Introducing Active Machine Learning FREE CHAPTER 3. Chapter 2: Designing Query Strategy Frameworks 4. Chapter 3: Managing the Human in the Loop 5. Part 2: Active Machine Learning in Practice
6. Chapter 4: Applying Active Learning to Computer Vision 7. Chapter 5: Leveraging Active Learning for Big Data 8. Part 3: Applying Active Machine Learning to Real-World Projects
9. Chapter 6: Evaluating and Enhancing Efficiency 10. Chapter 7: Utilizing Tools and Packages for Active ML 11. Index 12. Other Books You May Enjoy

Designing Query Strategy Frameworks

Query strategies act as the engine that drives active ML and determines which data points get selected for labeling. In this chapter, we aim to provide a comprehensive and detailed explanation of the most widely used and highly effective query strategy frameworks that are employed in active ML. These frameworks play a crucial role in the field of active ML, aiding in selecting informative and representative data points for labeling. The strategies that we will delve into include uncertainty sampling, query-by-committee, expected model change (EMC), expected error reduction (EER), and density-weighted methods. By thoroughly understanding these frameworks and the underlying principles, you can make informed decisions when designing and implementing active ML algorithms.

In this chapter, you will gain skills that will equip you to design and deploy query strategies that extract maximum value from labeling efforts. You will gain intuition for matching...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at £16.99/month. Cancel anytime