K-Means has two major problems: – Number of clusters must be known
– Doesn't handle outliers But there's a solution! Introducing DBSCAN, a Density based clustering algorithm. Read more…
@akshay_pachaar
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DBSCAN: Density-Based Clustering Solution Beyond K-Means
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RAG Skills Course Recommendation from Top NLP Expert
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That's a wrap! If you're an AI Engineer looking to elevate your RAG skills, check out my friend Nirant's course. With over 10 years of experience in NLP, @NirantK is one of the top AI Engineers in India. Explore his course here:
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LlamaIndex: Leading Data Framework for LLM Applications
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LlamaIndex @llama_index is the leading data framework for building LLM applications! Check this out
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Mem0: Memory Layer for AI Applications
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Mem0 The memory layer for your AI Apps. Check this out https://
github.com/mem0ai/mem0 -
Latent Scope: Embedding Clustering Classification for Untagged Data
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Latent Scope Embedding → Clustering → Classification for untagged data! Check this out https://
github.com/enjalot/latent
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DSPy: Automatic Prompting Solution for All LLMs
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DSPy Automatic Prompting for EVERY LLM! Check this out
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Phoenix: AI logging setup in five lines of code
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Phoenix Setup AI logging in 5 lines of code! Check this out
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Ragas: The Pytest Framework for RAG Applications
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Ragas First demo'd by OpenAI at their dev day, Ragas is the Pytest for RAG Apps Check this out https://
ragas.io -
7 Python Libraries for Production RAG Applications
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7 amazing Python libraries for building production-ready LLM-powered RAG apps:
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Wrap-up: Python, Machine Learning, and AI Engineering Resources
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That's a wrap! If you interested in: – Python – Machine Learning – AI Engineering Find me → @akshay_pachaar Subscribe to my AI Engineering Newsletter: @ML_Spring Cheers!