Applied AI with LLMs
Create, Deploy, and Monetize Intelligent Applications
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Beschreibung
This book is a hands-on guide for builders who want to turn AI into real, working software. With just a bit of Python, you’ll learn how to connect with major LLM APIs like OpenAI, Google, and Anthropic, and create practical tools that solve real problems.
The book begins with a fresh perspective on large language models (LLMs), moving beyond casual chats to focus on automation, APIs, and intelligent microservices. You’ll quickly gain mastery over the essentials—accessing APIs, fine-tuning key parameters, and understanding operational constraints to ensure your projects run reliably. Building on this foundation, you’ll create five fully functional, real-world applications: a Scraper + Telegram Publisher to gather, process, and broadcast live updates; a Smart Email Generator to transform rough notes into polished, professional messages; an Automatic Summarizer to distill PDFs or web pages into concise insights; a Custom Knowledge Chatbot to answer queries from a domain-specific knowledge base; and a Semantic Search for Notes to retrieve information from personal archives using intelligent queries. The book concludes by guiding you through monetization strategies, including business models, deployment approaches, payment integration, and compliance considerations.
This book is your roadmap for anyone ready to move from idea to working AI products. Whether you’re a developer, tinkerer, or startup founder, you’ll gain the skills to turn LLM capabilities into tangible, market-ready tools.
What you will learn:
- How to connect with major LLM APIs and unlock their potential beyond simple chat.
- How to configure, tune, and reliably run LLM-powered applications.
- What are the techniques for building domain-specific chatbots, summarizers, and automation workflows.
- Practical strategies to monetize your AI projects, from business models to deployment
Who this book is for:
Designed for developers, data scientists, engineers, and AI enthusiasts ready to turn LLMs into real-world applications.
Explains how to turn AI into fully functional, API-powered apps that solve real-world problems Covers building production-ready micro-tools with minimal Python, from concept to deployment in record time Discover creative, unconventional ways to combine LLMs with automation for high-impact results
Autor*in
Furio Piccinini
Themen in »Applied AI with LLMs«
Large Language Models AI Automation projects Python AI Integration Prompt Engineering with Code Real World LLM Applications