Cross-Encoders Cross-Encoders take both the query and document together as input and output a similarity score between 0 and 1. Although cross-encoders produce highly accurate similarity scores, they are not scalable (explained in next tweet). 5/n
@akshay_pachaar
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Bi-Encoders in RAG: Efficiency and Scalability Benefits
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Bi-Encoders in RAG Bi-encoders are a great choice for embedding models! Why • Efficiency: Pre-compute embeddings for all documents and store them in a vector store.
• Scalability: Then use fast ANN to search over millions of vectors 4/n -
gptme: Open-Source AI Agent Tool for Your Terminal
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Your terminal just got smarter! Introducing gptme: an open-source tool that let's you run AI Agent in your terminal with local tools Here's why it's a game-changer: Free and open-source Runs code in your local environment Reads, writes, and edits files Browses
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Python ML/MLOps CV NLP LLMs AI Engineering Tutorials
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That's a wrap! If you interested in: • Python • ML/MLOps • CV/NLP • LLMs • AI Engineering Fine me → @akshay_pachaar Everyday, I share tutorials on the above topics! Cheers!!
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Free 530-Page Data Science E-book with 150+ Visual Lessons
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FREE Data Science E-book (530+ page), featuring over 150 essential lessons in data science and machine learning.
— Akshay 🚀 (@akshay_pachaar) 4 octobre 2024
Visually explained! ✨
Download here: https://t.co/s6Ob6Zcie8 pic.twitter.com/IMLRIfwFCMFREE Data Science E-book (530+ page), featuring over 150 essential lessons in data science and machine learning. Visually explained! Download here: http://
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Self-Attention in LLMs Visualized as Directed Graph
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Self-attention in LLMs represented as a directed graph!
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Python, Machine Learning, RAGs, and AI Engineering Resources
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If you interested in: – Python – Machine Learning – RAGs/Agents – AI Engineering Find me → @akshay_pachaar I also write a Newsletter on AI Engineering → @ML_Spring Cheers!
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DBSCAN Clustering: Density-Based Approach Without Predefined Clusters
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Applying DBSCAN doesn't get easier Notice that we don't need to worry about number of clusters in the data, it's determined based on density! Check this out
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DBSCAN Clustering Implementation with Dummy Data
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Now that we understand how DBSCAN works, let's see things in action Time for some code First we create some dummy data for clustering! Check this out
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DBSCAN Clustering: Points and Eps Reachability Explained
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Now all the points which are not outliers & within in eps reachability of each, become part of the same cluster. That's it, that's all that DBSCAN is about! Check this image