AI Engineering

Description

AI Engineering: Building Applications with Foundation Models (1st Edition) by Chip Huyen is a cutting-edge guide to modern AI development. This book explores AI Engineering principles, focusing on building scalable machine learning applications. It introduces foundation models and their role in advancing artificial intelligence solutions. Readers will learn how to integrate large-scale AI models into real-world applications. The book provides a practical approach to designing, deploying, and maintaining AI systems.

AI Engineering is essential for developers, engineers, and data scientists working with machine learning technologies. It covers key topics such as model deployment, infrastructure, and MLOps. The book explains how to optimize AI models for efficiency and scalability. Readers will discover best practices for data preprocessing, model selection, and continuous integration. It offers hands-on guidance for implementing AI pipelines using modern frameworks.

This book bridges the gap between research and real-world AI implementation. It provides strategies for overcoming challenges in AI deployment and automation. AI Engineering helps readers build robust AI-driven products and services. The book discusses ethical considerations, security concerns, and responsible AI development. It emphasizes the importance of designing AI applications with transparency and fairness.

With a strong focus on production-ready AI systems, this book prepares readers for industry challenges. It includes case studies from leading AI-driven companies. The book offers step-by-step coding examples for practical learning and implementation. Readers will gain expertise in working with foundation models for large-scale AI solutions. AI Engineering is a must-read for anyone looking to master applied artificial intelligence.