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This book is a practical guide for anyone interested in diving into the world of Generative AI development, regardless of their prior programming experience.

How This Book Stands Out

When writing this book, we focused on two main goals: creating a clear, practical roadmap and striking a good balance between theory and hands-on practice. Unlike other books that can get lost in theory or assume you need advanced technical skills, this book is tailored for both beginners and advanced users. We place a special emphasis on using local LLM inference and developing AI-driven applications—something that’s now more affordable thanks to the newly released LLMs for edge computing. Our key takeaway: You don’t need to be a machine learning expert to learn Generative AI.

Here's what you can expect:

Clear and concise explanations: Complex AI concepts are broken down into simple, digestible steps, making this book accessible to anyone, regardless of technical background.
Hands-On Projects: Each chapter guides you through building specific AI applications, from setting up your environment to deploying your final product.
Real-World Applications: Learn through practical examples that solve real problems, giving you valuable experience in applying AI techniques.
Essential Tools & Libraries: Master popular tools like Langchain, Vanna, TensorFlow, and PyTorch, giving you in-demand skills to thrive in the AI space.
Project-Based Learning: Work on engaging projects ranging from image recognition to advanced LLM fine-tuning, reinforcing your knowledge with hands-on practice.
Advance Topics: Explore cutting-edge techniques such as the Model Context Protocol (MCP), Google A2A, and Minions for integrating local LLMs with remote models. Learn how to optimize performance for edge computing, coordinate advanced multi-model orchestration, and build real-time AI applications.

By the end of this book, you'll be able to:

Grasp the fundamentals of Generative AI and Large Language Models (LLMs).
Efficiently set up and use local LLM inference for AI development.
Enrich RAG (Retrieval Augmented Generation) models with your own data, like PDFs and documents.
Integrate LLM models with SQL databases for more dynamic AI solutions.
Build and train your own AI models from scratch.
Use AI agents to perform tasks autonomously.
Deploy your AI applications in real-world environments confidently.
Apply advanced techniques like the Model Context Protocol (MCP), Google A2A and Minion(s) protocol for seamless local-to-cloud communication.

This book offers a comprehensive roadmap for anyone, whether you're a student, a professional, or simply curious about AI—providing the tools and confidence to create innovative AI solutions. Start your AI journey today and turn your ideas into reality!

The book was first published on October 4, 2024, and has been continuously updated with new content based on the growing interest in Generative AI. Once you purchase the book, you will receive notifications whenever updates are made. Happy reading!

If you are not sure if this book is for you, I suggest you read the sample chapter of the book. The sample chapter is available in different formats including HTML. Anyway, I encourage you to try it out, and if you don't like the book, you can always ask a 100% refund within 60 days.

The source code for the examples in the book is available on GitHub.

We need your feedback!

We would like to hear what you think, what you like or dislike the content of the book. Your feedback will help us to write a better book and help others to clear all the concepts. To submit your feedback, please use the feedback link below.

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