Achieve your goals faster with our ✨NEW✨ Personalized Learning Plan - select your content, set your own timeline and we will help you stay on track. Log in and Head to My Learning to get started! Learn more

Offered By: IBMSkillsNetwork

Boosting NLP performance through text augmentation

Unlock powerful text augmentation techniques using Python, NLPAug, and transformers in this hands-on project. Implement Easy Data Augmentation (EDA), back-translation, and NLP augmentation with LLMs to diversify text datasets. This tutorial offers practical skills to enhance your machine learning model's robustness and performance by generating varied training data, reducing overfitting, and improving accuracy in just 45 minutes.

Continue reading

Guided Project

Machine Learning

5.0
(1 Review)

At a Glance

Unlock powerful text augmentation techniques using Python, NLPAug, and transformers in this hands-on project. Implement Easy Data Augmentation (EDA), back-translation, and NLP augmentation with LLMs to diversify text datasets. This tutorial offers practical skills to enhance your machine learning model's robustness and performance by generating varied training data, reducing overfitting, and improving accuracy in just 45 minutes.

Understanding and implementing text augmentation is a crucial skill for anyone involved in Natural Language Processing (NLP). This guided project will equip you with the tools to diversify your datasets, making your machine learning models more robust, less prone to overfitting, and ultimately more accurate. By mastering text augmentation techniques such as Easy Data Augmentation, back-translation, and text augmentation from contextual embeddings, you will be able to enhance the performance of your ML models significantly.

This project is ideal for data scientists and NLP enthusiasts who want to gain practical skills. By the end of this hands-on tutorial, you will have a deeper understanding of how to manipulate and improve text data for better model training, giving you a competitive edge in the field of machine learning.

What you'll learn


After you complete the project, you will be able to:

  • Understand the importance and impact of text augmentation in NLP.
  • Implement EDA, back-translation, and contextual text augmentation techniques using Python, NLPAug, and transformers.
  • Generate varied training data to reduce overfitting and improve the accuracy of your machine learning models.
  • Apply these augmentation techniques to real-world datasets, specifically a movie review dataset for sentiment analysis.

What you'll need


Before starting this guided project, you should have:

  • Basic knowledge of Python programming.
  • A current version of Chrome, Edge, Firefox, Internet Explorer, or Safari for the best platform experience.

Dive into this project and enhance your machine learning model's robustness and performance by mastering text augmentation techniques today!

Estimated Effort

45 Minutes

Level

Beginner

Skills You Will Learn

Generative AI, NLP, Python, Scikit-learn, Text Augmentation, Transformers

Language

English

Course Code

GPXX0LJDEN

Tell Your Friends!

Saved this page to your clipboard!

Have questions or need support? Chat with me 😊