Name: AI Engineering in Practice
Brand: Manning
SKU: 9781633436305
Availability: InStock

AI Engineering in Practice

Design prompts that generate accurate and readable responses from LLMs
Mitigate hallucinations in LLM output
Domain-aware content generation using RAG

SKU: 9781633436305 Categories: Best Sellers, Manning Brand: Manning

Description

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Generative AI models such as ChatGPT, Stable Diffusion, and Gemini can produce amazingly “human-like” news articles, document summaries, images, computer code, and more—if you know how to write effective prompts. This book will teach you the prompt design and authoring skills you need to get useful and relevant responses from AI models, along with advanced prompting techniques for Retrieval Augmented Generation (RAG), building autonomous agents, and data privacy.

AI Engineering in Practice teaches you how to:

Design prompts that generate accurate and readable responses from LLMs
Mitigate hallucinations in LLM output
Domain-aware content generation using RAG
How AI model design affects your prompts
Evaluate, optimize, and organize your prompts

Prompt engineering is the discipline of writing instructions for AI models to generate relevant, accurate, and usable completions. AI Engineering in Practice shows you how to engineer prompts that ensure the outputs of LLMs and other generative AI models exactly match your requirements. You’ll learn how to structure your objectives, take advantage of contextual details, and even pick the right model for your task.

about the book

AI Engineering in Practice introduces valuable prompt engineering techniques based on industry usage and AI research. You’ll learn by exploring real-world cases and examples, from simple tasks like generating formal emails, to using LLMs for data annotation, classifying tech support tickets, and building custom chatbots. You’ll appreciate author Richard Davies’ explanation of prompt design patterns and templates that you can customize for your own needs. Along the way, you’ll discover automated prompting techniques you can use to create autonomous AI agents, and methods for evaluating your own prompts to ensure they’re delivering the quality outputs you desire.