This repository aggregates frameworks, tutorials, and tooling references covering the full LLM development lifecycle from pretraining through deployment. It organizes resources into categories including fine-tuning with techniques like DPO, prompt engineering, model serving infrastructure, and LLMOps for monitoring and evaluation. The handbook serves as a reference guide for building production-grade LLM applications, with sections spanning foundational ML concepts, application frameworks, and operational best practices.