Guide Outlines Data Engineering For Large Models

A new book titled 'Data Engineering for Large Models: Architecture, Algorithms, and Project Practice' outlines infrastructure, algorithms, and a six-part curriculum for preparing datasets for large models. It covers infrastructure, text pre-training, multimodal processing, alignment and synthetic data, application-level RAG/agents, and five capstone projects with runnable code. The book emphasizes data quality, deduplication, multimodal pipelines, and synthetic instruction generation for production-ready training.