Book details

Data Engineering for Large Models: Architecture, Algorithms, and Project Practice

Categories Data science , LLMs , Deep learning , Artificial intelligence , Machine Learning , MLOps , Natural language processing

This handbook covers data engineering across the lifecycle of large foundation models, from infrastructure and pre-training data to instruction tuning, synthetic data, and deployment. Its 14-part structure includes multimodal data, reasoning and agent data, data operations, privacy, open-source recipes, and practical projects.