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Data-Centric Machine Learning with Python

You're reading from   Data-Centric Machine Learning with Python The ultimate guide to engineering and deploying high-quality models based on good data

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Product type Paperback
Published in Feb 2024
Publisher Packt
ISBN-13 9781804618127
Length 378 pages
Edition 1st Edition
Languages
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Authors (3):
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Jonas Christensen Jonas Christensen
Author Profile Icon Jonas Christensen
Jonas Christensen
Manmohan Gosada Manmohan Gosada
Author Profile Icon Manmohan Gosada
Manmohan Gosada
Nakul Bajaj Nakul Bajaj
Author Profile Icon Nakul Bajaj
Nakul Bajaj
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Toc

Table of Contents (17) Chapters Close

Preface 1. Part 1: What Data-Centric Machine Learning Is and Why We Need It FREE CHAPTER
2. Chapter 1: Exploring Data-Centric Machine Learning 3. Chapter 2: From Model-Centric to Data-Centric – ML’s Evolution 4. Part 2: The Building Blocks of Data-Centric ML
5. Chapter 3: Principles of Data-Centric ML 6. Chapter 4: Data Labeling Is a Collaborative Process 7. Part 3: Technical Approaches to Better Data
8. Chapter 5: Techniques for Data Cleaning 9. Chapter 6: Techniques for Programmatic Labeling in Machine Learning 10. Chapter 7: Using Synthetic Data in Data-Centric Machine Learning 11. Chapter 8: Techniques for Identifying and Removing Bias 12. Chapter 9: Dealing with Edge Cases and Rare Events in Machine Learning 13. Part 4: Getting Started with Data-Centric ML
14. Chapter 10: Kick-Starting Your Journey in Data-Centric Machine Learning 15. Index 16. Other Books You May Enjoy

Technical requirements

To execute the code examples provided in this chapter on programmatic labeling techniques, ensure that you have the following technical prerequisites installed in your Python environment:

Python version

The examples in this chapter require Python version 3.7 or higher. You can check your Python version by running the following:

import sys
print(sys.version)

We recommend using the Jupyter Notebook integrated development environment (IDE) for an interactive and organized coding experience. If you don’t have it installed, you can install it using this line:

pip install jupyter

Launch Jupyter Notebook with the following command:

jupyter notebook

Library requirements

Ensure that the following Python packages are installed in your environment. You can install them using the following commands:

pip install snorkel
pip install scikit-learn
pip install Pillow
pip install tensorflow
pip install pandas
pip install numpy

Additionally,...

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