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A hands-on walkthrough of embeddings and similarity search using FIFA player data. Most of us who have played around with generative AI are familiar with building a RAG (or Retrieval Augmented Generation) model. In essence, you import your source documents to create a corpus, chunk the text into smaller pieces, and send those chunks into an embedding model to generate numerical vectors. From there, your query searches the vector database for relevant chunks, which are then

I know that I sound like a broken record when I say this – I love mixing passions. A couple of years ago I decided to make the jump into AI, but I have been a fan of movies for almost two decades. I review movies at my website IHATEBadMovies.com and at this writing I have over 1,500 reviews. If you feel so inclined, you can find my code here. As part of my AI / Machine Learning journey, I decided that I wanted to take a deeper dive into recommendation systems. I am sure