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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

Exploring Label Studio

Label Studio (https://labelstud.io/) is an open source data labeling and annotation platform designed to streamline the process of labeling diverse data types, including images, text, and audio. With a user-friendly interface, Label Studio empowers machine learning practitioners and data scientists to efficiently label and annotate datasets for training and evaluating models. Its versatility, collaborative features, and support for multiple labeling tasks make it a valuable tool in the development of robust and accurate machine learning models.

In this section, we are going to label four types of data: image, video, text, and audio.

Labeling the image data

Let us label the image data using Label Studio.

Once you have installed the Label Studio tool using the pip command as given in the Technical requirements section, start Label Studio, go to the browser, and type in the following URL: http://localhost:8080/. As we have deployed Label Studio using...

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