practical-mlops-book

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llm-twin-course is a free course that teaches how to build a production-ready LLM and RAG system using LLMOps best practices. It provides source code and hands-on lessons for creating an AI replica. The course covers data gathering to productionizing LLMs.

LLM-Engineers-Handbook is a practical guide for building end-to-end LLM-based systems. It covers data collection, LLM training pipelines, RAG systems, and AWS deployment. The handbook provides best practices for LLMOps and creating production-ready AI applications.

hivemind is a PyTorch library for decentralized deep learning. It enables training AI models across the internet using distributed computing. The platform is designed for collaborative AI research and development, allowing researchers to leverage the power of thousands of volunteers.

Generative-AI-with-LLMs is a learning resource focused on the fundamentals of Generative AI and Large Language Models (LLMs). It teaches how to deploy generative AI in real-world applications. The course covers data gathering, model selection, and performance evaluation.

VectorHub is a free, open-source learning website for adding vector retrieval to ML stacks. It provides practical resources for creating MVPs and solving use-case-specific challenges. The platform is designed for software developers and machine learning architects.