Text Embeddings, Classification, and Semantic Search (w/ Python Code)

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In this video, I introduce text embeddings and describe how we can use them for 2 simple yet high-value use cases: text classification and semantic search.

More Resources:
🎥 RAG: https://youtu.be/Ylz779Op9Pw
📰 Read more: https://medium.com/towards-data-science/text-embeddings-classification-and-semantic-search-8291746220be?sk=03e4e68a420373a3525de8721f57c570
💻 GitHub: https://github.com/ShawhinT/YouTube-Blog/tree/main/LLMs/text-embeddings

▶️ Series Playlist: https://www.youtube.com/playlist?list=PLz-ep5RbHosU2hnz5ejezwaYpdMutMVB0

[1] https://youtu.be/A8HEPBdKVMA?si=PA4kCnfgd3nx24LR
[2] R. Patil, S. Boit, V. Gudivada and J. Nandigam, “A Survey of Text Representation and Embedding Techniques in NLP,” in IEEE Access, vol. 11, pp. 36120–36146, 2023, doi: 10.1109/ACCESS.2023.3266377.
[3] https://owasp.org/www-project-top-10-for-large-language-model-applications/

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Homepage: https://www.shawhintalebi.com/

Intro - 0:00
Problem: Text isn't computable - 0:42
Text Embeddings - 1:42
Why should I care? - 3:15
Use Case 1: Text Classification - 5:49
Use Case 2: Semantic Search - 12:40
Free gift for watching: 23:50