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FAISS Vector Library with LangChain and OpenAI (Semantic Search)



In this video, we take a look at the Facebook AI Similarity Search (FAISS) vector library. Through a few examples, we will grab a document, chunk it, set up embeddings, and search through it.

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Email: [email protected]
Website & Blog: https://ryannolandata.com/

WATCH NEXT
OpenAI/Langchain Playlist: https://www.youtube.com/watch?v=5qP6u-WGSPk&list=PLcQVY5V2UY4Kat6vxC7ESzIIzHWdwlnak&ab_channel=RyanNolanData
Vector Embeddings: https://www.youtube.com/watch?v=xdr5ByCpnd4&ab_channel=RyanNolanData
Langchain Chains: https://www.youtube.com/watch?v=gQnJEjiaHFw&ab_channel=RyanNolanData
Streamlit Langchain: https://www.youtube.com/watch?v=qXcMGBj4i3A&feature=youtu.be

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*Practice SQL & Python Interview Questions: https://stratascratch.com/?via=ryan

WHO AM I?
As a full-time data analyst/scientist at a fintech company specializing in combating fraud within underwriting and risk, I’ve transitioned from my background in Electrical Engineering to pursue my true passion: data. In this dynamic field, I’ve discovered a profound interest in leveraging data analytics to address complex challenges in the financial sector.

This YouTube channel serves as both a platform for sharing knowledge and a personal journey of continuous learning. With a commitment to growth, I aim to expand my skill set by publishing 2 to 3 new videos each week, delving into various aspects of data analytics/science and Artificial Intelligence. Join me on this exciting journey as we explore the endless possibilities of data together.

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NEO 1X Robot, OpenAI chips, The AI Scientist, and the future of prompt engineering