My Courses
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Hands-on Guide to Langfuse for LLM-Based Applications
Explore Langfuse’s powerful tools for building and managing LLM applications in Python, focusing on key features.
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Enhancing Retrieval-Augmented Generation in NLP with CRAG
Learn how CRAG benchmarks Retrieval-Augmented Generation (RAG) systems for reliable and creative question-answering in NLP.
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Integrating CrewAI and Ollama for Building Intelligent Agents
Discover how CrewAI and Ollama collaborate to create intelligent, efficient AI agents for complex task management.
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Nomic Embeddings and Their Integration with LlamaIndex
Enhance AI with Nomic Embeddings and LlamaIndex for efficient, semantic data handling and retrieval.
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Hands-On Guide to Running LLMs Locally using Ollama
Explore how Ollama enables local execution of large language models for enhanced privacy and cost savings.
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Thought-Augmented Reasoning through Buffer of Thoughts (BoT)
Enhance the robustness and accuracy of LLM through thought-augmented reasoning based on the Buffer of Thought approach.
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How Does RAG Enhance the Contextual Understanding of LLMs?
RAG elevates understanding: integrating external knowledge sources into language model generation process
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Observing and Examining AI Agents through AgentOps
Explore how AgentOps monitors, debugs, and tracks costs for LLM-based AI agents in various contexts.
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Self-Organising File Management Through LlamaFS
Implement LlamaFS, an AI-driven file management system, based on Llama3 and Groq.
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GNN-RAG: Enhancing the Reasoning Capabilities of LLMs using GNNs
GNN-RAG, a recent development, synergises GNNs and LLMs to excel in KGQA.
