Natural Language Processing (NLP) Concepts

from Generative AI 101 · host Emily Laird

In this episode of Generative AI 101, we break down the fundamental concepts of Natural Language Processing (NLP). Imagine trying to read a book that's one long, unbroken string of text—impossible, right? That’s where tokenization comes in, breaking text into manageable chunks. We’ll also cover stemming and lemmatization, techniques for reducing words to their root forms, and explain the importance of stop words—the linguistic background noise. Finally, we’ll explore Named Entity Recognition (NER), which identifies key names and places in text. These basics form the foundation of NLP, making our interactions with technology smoother and more intuitive. Connect with Emily Laird on LinkedIn

Episode metadata supplied by the publisher feed · Published Jul 1, 2024

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Natural Language Processing (NLP) Concepts

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