🔥 Welcome to MyBunny.TV – Premium Entertainment at Your Fingertips 🔥
Enjoy 35,000+ Premium HD Channels, Premium HD Channels, Thousands of movies & series, No buffering, no delays, and experience instant activation.
Reliable, stable, and built for the ultimate streaming experience – no hassles, just entertainment! MyBunny.TV – Cheaper Than Cable • Up to 30% Off Yearly Plans • All NFL, ESPN, PPV Events Included 🔥
🎉 Join the fastest growing IPTV community today and discover why everyone is switching to MyBunny.TV!
Minnick C. A Developer's Guide to Integrating Generative AI into Apps 2026
To start this P2P download, you have to install a BitTorrent client like
qBittorrent
Category:Other Total size: 17.96 MB Added: 23 hours ago (2026-02-10 08:33:01)
Share ratio:119 seeders, 7 leechers Info Hash:3D21F56178A5659740376BA44035FE257B0F0675 Last updated: 15 minutes ago (2026-02-11 07:56:52)
Report Bad Torrent
×
Description:
Textbook in PDF format
Create, implement, and scale commercially successful Generative AI applications that solve real-world problems.
In A Developer's Guide to Integrating Generative AI into Applications, software developer, technology educator, and author Chris Minnick explain exactly how to design and implement scalable generative AI applications. The book walks you through building production-ready GenAI applications, covering the key architectural choices, integration patterns, and design practices needed to deliver accurate, efficient, and commercially viable solutions.
Minnick demonstrates the principles and techniques you need to succeed in the rapidly evolving GenAI space in real-world business environments. He shows how to overcome the practical challenges developers face when embedding generative AI into products, from designing effective prompts to managing performance and cost, with hands-on examples that demonstrate proven techniques you can apply immediately.
You’ll discover:
Step-by-step guides to using AI APIs, SDKs, AI-generated data, and synthetic users
Up-to-date explanations of how to build AI-powered chatbots and assistants, AI-driven content-enhancement services, code generation and software development tools, and AI search and recommendation utilities
How to improve your interface and UX design with AI features
Explorations of business and scaling considerations, including how to monetize AI features, how to optimize AI for both performance and cost, and case studies of successful products that incorporate GenAI
Perfect for software developers, product managers, engineering leaders, and UX designers, A Developer's Guide to Integrating Generative AI into Applications is your essential guide to integrating Generative AI into real products and creating the AI-powered applications that will define the next era of software.
Who Should Read This Book:
This is a developer’s guide. The intended audience is software developers who want to learn how to build applications that make use of AI—generative AI in particular. The book doesn’t assume that you have much, or any, prior experience with creating AI models or developing applications that make use of AI. If you have some knowledge of Python or JavaScript, that will be helpful for understanding and running the sample code in the book. But if you have experience in any programming language, you’ll be able to follow the book’s step-by-step instructions to pick up enough knowledge to apply the lessons using your language of choice. Heck, you might even ask an AI coding assistant to help you run, debug, and modify the book’s code.
Most importantly, the ideal reader of this book is someone who’s curious and who has an open mind about the possibilities of creating new types of applications that haven’t been previously possible, but who also has a healthy skepticism about the extent to which AI can replace software developers.
Introduction
Part I: Foundations of Generative AI
CHAPTER 1: Introduction to Generative AI
Evolution of AI Applications
Understanding AI and ML
What Makes Generative AI Different?
Real-World Examples of AI Integration
Summary
CHAPTER 2: Understanding Generative AI Models
Key Factors in Choosing a Model
Proprietary Models
Open and Open-Source Models
Deciding Between Proprietary and Open Models
Adapting Your Model’s Abilities
When to Use Non-Generative Models Alongside GenAI
Summary
CHAPTER 3: Getting Started with AI APIs and SDKs
Exploring Hosted Models
GenAI Integration Patterns
Summary