GitHub - chiphuyen/aie-book: [WIP] Resources for AI engineers. Also contains supporting materials for the book AI Engineering (Chip Huyen, 2025)
2 hours ago
- #AI Engineering
- #Machine Learning
- #Foundation Models
- 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.