Why I stopped using Vector Search alone?
How I improved RAG context precision from 68% to 85% by going beyond vector search, combining semantic and keyword retrieval to handle queries that embeddings alone get wrong.
Blog
Writing
Thoughts on RAG systems, production ML, and the messy reality of getting models to actually work. Published on Medium ↗
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Triplet Loss: Your Key to Unlocking the Similarities in Your Data Using TF
A deep dive into contrastive learning with Triplet Loss, with hands-on TensorFlow examples for similarity learning tasks.
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Demystifying Named Entity Recognition in TensorFlow
Unveiling the magic behind "Who, What, Where": a practical guide to NER with TensorFlow.
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Are you struggling to stay productive?
You're not alone. There's a lot going on in the world right now. Here's how to stay focused when the days are getting shorter.
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