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Active Machine Learning with Python

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

Product type Paperback

Published in Mar 2024

Publisher Packt

ISBN-13 9781835464946

Length 176 pages

Edition 1st Edition

Languages

Python

Concepts

Machine Learning

Author (1):

Margaux Masson-Forsythe

View More author details

Table of Contents (13) Chapters

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

Why subscribe?

12. Other Books You May Enjoy

Technical requirements

For the code examples demonstrated in this chapter, we have used Python 3.9.6 with the following packages:

numpy (version 1.23.5)
scikit-learn (version 1.2.2)
matplotlib (version 3.7.1)

The rest of the chapter is locked

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Authors (1)

Margaux Masson-Forsythe

Margaux Masson-Forsythe

Margaux Masson-Forsythe is a skilled machine learning engineer and advocate for advancements in surgical data science and climate AI. As the Director of Machine Learning at Surgical Data Science Collective, she builds computer vision models to detect surgical tools in videos and track procedural motions. Masson-Forsythe manages a multidisciplinary team and oversees model implementation, data pipelines, infrastructure, and product delivery. With a background in computer science and expertise in machine learning, computer vision, and geospatial analytics, she has worked on projects related to reforestation, deforestation monitoring, and crop yield prediction.

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