A practical, end-to-end tutorial on instruction tuning LLMs: data design, LoRA/QLoRA training code, evaluation, deployment, and production tips.
Build an AI-powered competitor analysis API with RAG, embeddings, orchestration, and guardrails—architecture, code patterns, KPIs, and governance.
Build a practical GraphRAG pipeline: extract a knowledge graph, index nodes and chunks, retrieve local paths and global summaries, and synthesize grounded answers.
Build a production-ready AI meeting transcription API with streaming, diarization, summaries, and exports. Code samples and architecture included.
Practical blueprint for an AI content personalization API: architecture, endpoints, models, metrics, latency, and safety—built to scale.
Build a production-ready AI email assistant: architecture, Gmail/Graph integration, LLM prompts, security, reliability, and code examples.
