Python

Explore multimodal AI models like LLaVA, GPT-4V, and Qwen-VL that understand both images and text, with practical code examples.

A practical guide to LLM quantization techniques for running large models on consumer hardware with minimal quality loss.

Learn how to run open-source LLMs locally using Ollama and vLLM for privacy, cost savings, and low-latency inference.

A practical comparison of LangChain and LlamaIndex for building LLM-powered applications with code examples for common use cases.

Master the art of prompt engineering with techniques like chain-of-thought, few-shot learning, and structured outputs to get better results from LLMs.

A comprehensive guide to building Retrieval Augmented Generation (RAG) systems that combine the power of LLMs with your own knowledge base.

A practical guide to vector databases for semantic search and RAG applications, comparing popular options like Pinecone, Weaviate, ChromaDB, and Qdrant.

Learn how to build named entity recognition systems using spaCy, transformers, and custom training for domain-specific entities with complete, production-ready code.

A comprehensive guide to text embeddings covering Word2Vec, GloVe, FastText, and modern sentence transformers like SBERT with complete, runnable code examples.

Comprehensive guide to OpenCV for computer vision applications, covering image processing, feature detection, object tracking, and real-time video analysis with practical examples.

Understanding ArcFace loss - the breakthrough technique that revolutionized face recognition by teaching networks to create better feature boundaries through angular margins.

Quick setup to get everything installed on your local machine for tensorflow and pytorch

I go through my experience attending the Melbourne Datathon 2016 and placing 4th.