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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

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Product type Paperback
Published in Mar 2024
Publisher Packt
ISBN-13 9781835464946
Length 176 pages
Edition 1st Edition
Languages
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Author (1):
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Margaux Masson-Forsythe Margaux Masson-Forsythe
Author Profile Icon Margaux Masson-Forsythe
Margaux Masson-Forsythe
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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

Technical requirements

In this chapter, you will need to install the Ultralytics, PyYAML, and Roboflow packages.

Ultralytics is a popular open source Python library for building high-performance computer vision and deep learning models. It provides implementations of state-of-the-art object detection and image segmentation models including YOLO that can be trained on custom datasets.

PyYAML is a Python library used for reading and writing YAML files. YAML is a human-readable data serialization format. PyYAML allows loading YAML data from files or strings into Python data types such as dictionaries and lists. It can also dump Python objects back into YAML strings.

Roboflow, as presented in earlier chapters, is a platform that helps with preparing and managing datasets for computer vision models. It provides tools to annotate images, create training/test splits, and export labeled datasets in formats that are usable by deep learning frameworks such as PyTorch. Roboflow also...

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