Machine Learning & AI Tutorials¶

Objective: Master complex machine learning and AI implementations through step-by-step guides. When you need to implement specific ML/AI technologies, when you want to follow proven patterns, when you need copy-paste runnable examples—these tutorials become your weapon of choice.

ML Operations¶

• MLflow API Experiments - Master MLflow for experiment tracking and model management
• ONNX Browser Inference - Deploy machine learning models directly in the browser
• RAG with Ollama + Database - Build intelligent data interfaces with retrieval-augmented generation
• MCP ↔ MLflow Toolchain - Data-agnostic LLM experimentation with Model Context Protocol
• Semantic ML Training - Master semantic machine learning from embeddings to production

Local LLM Deployments¶

• Local LLM Deployments (Ollama, llama.cpp, vLLM, TGI) - Methods, quantization, OpenAI-compatible serving, RAG, and benchmarks

These tutorials provide the complete machinery for implementing key machine learning and AI technologies and workflows. Each guide includes production-ready examples, configuration files, and best practices for enterprise deployment.