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Applying AI to Text Data

### Introduction to Machine Learning with Text Data In this lab, **"Applying ML to Text Data,"** you’ll learn how to process and analyze text using machine learning techniques. Start by understanding the basics of text data representation and explore key preprocessing methods like stopword removal and lemmatization to prepare text for analysis. You’ll then explore different encoding methods, including one-hot encoding, TF-IDF, and word embeddings, to transform text into numerical formats that machine learning models can understand. Finally, you’ll apply these techniques to build a sentiment analysis classifier, gaining hands-on experience with a foundational NLP task. This lab is an accessible introduction to working with text data in machine learning, providing the foundational skills you need to tackle more advanced tasks.

Labs

Path Info

Level
Clock icon Intermediate
Duration
Clock icon 30m
Published
Clock icon Dec 13, 2024

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Danny Sullivan is a former special education teacher and professional baseball player that moved into software development in 2014. He’s experienced with Ruby, Python and JavaScript ecosystems, but enjoys Ruby most for its user friendliness and rapid prototyping capabilities.

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