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Data Labeling in Machine Learning with Python

You're reading from  Data Labeling in Machine Learning with Python

Product type Book
Published in Jan 2024
Publisher Packt
ISBN-13 9781804610541
Pages 398 pages
Edition 1st Edition
Languages
Author (1):
Vijaya Kumar Suda Vijaya Kumar Suda
Profile icon Vijaya Kumar Suda

Table of Contents (18) Chapters

Preface Part 1: Labeling Tabular Data
Chapter 1: Exploring Data for Machine Learning Chapter 2: Labeling Data for Classification Chapter 3: Labeling Data for Regression Part 2: Labeling Image Data
Chapter 4: Exploring Image Data Chapter 5: Labeling Image Data Using Rules Chapter 6: Labeling Image Data Using Data Augmentation Part 3: Labeling Text, Audio, and Video Data
Chapter 7: Labeling Text Data Chapter 8: Exploring Video Data Chapter 9: Labeling Video Data Chapter 10: Exploring Audio Data Chapter 11: Labeling Audio Data Chapter 12: Hands-On Exploring Data Labeling Tools Index Other Books You May Enjoy

Data labeling using Snorkel

In this section, we are going to learn what Snorkel is and how we can use it to label data in Python programmatically.

Labeling data is an important step of a data science project and critical for training models to solve specific business problems.

In many real-world cases, training data does not have labels, or very little data with labels is available. For example, in a housing dataset, in some neighborhoods, historical housing prices may not be available for most of the houses. Another example, in the case of finance, is all transactions may not have an associated invoice number. Historical data with labels is critical for businesses to train models and automate their business processes using machine learning (ML) and artificial intelligence. However, this requires either outsourcing the data labeling to expensive domain experts or the business waiting for a long time to get new training data with labels.

This is where Snorkel comes into the...

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