GitHub - chiphuyen/aie-book: [WIP] Resources for AI engineers. Also contains supporting materials for the book AI Engineering (Chip Huyen, 2025)

4 hours ago

The availability of foundation models has made AI accessible as a development tool for all.
The book provides an end-to-end framework for adapting foundation models, including LLMs and LMMs, to real-world problems.
It addresses key questions in AI application development, such as evaluation, hallucinations, prompt engineering, RAG, agents, finetuning, data validation, efficiency, and security.
The content is based on case studies, references, and expert reviews, drawing from the author's decade of experience in ML and language models.
This book focuses on fundamentals of AI engineering rather than specific tools, ensuring lasting relevance.
It complements 'Designing Machine Learning Systems' (DMLS), covering foundation models while DMLS focuses on traditional ML, with both being self-contained.
Target audience includes AI engineers, data scientists, managers, and product managers involved in building or optimizing AI applications.
The book also benefits tool developers, researchers, job candidates, and those seeking to understand AI's capabilities and limitations.
Technical depth is provided in some sections, with warnings for readers to skip if desired.
It includes praise from industry experts and acknowledges numerous contributors for their feedback and support.

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