My Courses
Long-Context Comprehension with Dual Chunk Attention (DCA) in LLMs
Dual Chunk Attention optimizes large language models for efficient processing of extensive text sequences and long contexts.
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.
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.
Integrating CrewAI and Ollama for Building Intelligent Agents
Discover how CrewAI and Ollama collaborate to create intelligent, efficient AI agents for complex task management.
Nomic Embeddings and Their Integration with LlamaIndex
Enhance AI with Nomic Embeddings and LlamaIndex for efficient, semantic data handling and retrieval.
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.
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.
How Does RAG Enhance the Contextual Understanding of LLMs?
RAG elevates understanding: integrating external knowledge sources into language model generation process
Observing and Examining AI Agents through AgentOps
Explore how AgentOps monitors, debugs, and tracks costs for LLM-based AI agents in various contexts.
Self-Organising File Management Through LlamaFS
Implement LlamaFS, an AI-driven file management system, based on Llama3 and Groq.
