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

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Published inJan 2024

PublisherPackt

ISBN-139781804610541

Edition1st Edition

Concepts

Machine Learning

Author (1)

Vijaya Kumar Suda

Tools and frameworks for text data labeling

There are several open source tools and frameworks available for text data analysis and labeling. Here are some popular ones, along with their pros and cons:

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Data Labeling in Machine Learning with Python

Published in: Jan 2024Publisher: PacktISBN-13: 9781804610541

Author (1)

Vijaya Kumar Suda

Vijaya Kumar Suda is a seasoned data and AI professional boasting over two decades of expertise collaborating with global clients. Having resided and worked in diverse locations such as Switzerland, Belgium, Mexico, Bahrain, India, Canada, and the USA, Vijaya has successfully assisted customers spanning various industries. Currently serving as a senior data and AI consultant at Microsoft, he is instrumental in guiding industry partners through their digital transformation endeavors using cutting-edge cloud technologies and AI capabilities. His proficiency encompasses architecture, data engineering, machine learning, generative AI, and cloud solutions.
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Tools and frameworks

Pros

Cons

Natural Language Toolkit (NLTK)

Comprehensive library for NLP tasks.

Rich set of tools for tokenization, stemming, tagging, parsing, and more.

Active community support.

Suitable for educational purposes and research projects.

Some components may not be as efficient for large-scale industrial applications.

Steep learning curve for beginners.

spaCy

Fast and efficient, designed for production use.

Pre-trained models for various languages.

Provides robust support for tokenization, named entity...

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Tools and frameworks for text data labeling

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