Email the Author
You can use this page to email Shamim Bhuiyan and Timur Isachenko about Generative AI with local LLM.
About the Book
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: Dive deeper into cutting-edge techniques like the Model Context Protocol (MCP), integrating local LLMs with remote models (Minions), and optimizing performance for edge computing. Explore advanced multi-model orchestration, and 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) 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.
About the Authors
Shamim Bhuiyan, currently working as an Enterprise architect, where he is responsible for designing and building out high scalable, high load middleware solutions. He has been in the IT field for over 16 years and specialized in Java and Data science. Also, he is a former SOA solution designer, speaker, and Big data evangelist. Actively participates in the development and designing high-performance software for IT, telecommunication and banking industry. In spare times, he usually writes blogs #frommyworkshop and shares ideas with others.
Timur Isachenko is a Technical Lead and Solution Architect at Solvd, with 15+ years of experience in backend development and high-load systems across finance, healthcare, and online banking. He holds a Specialist Degree in Computer Science and Applied Mathematics from Kuban State University.
He has led projects in education, betting, and enterprise integrations and co-authored High Performance In-Memory Data Grid with Ignite. A frequent conference speaker, he shares insights on scalable architectures.
Outside work, Timur is a father of three and an avid runner, once running every day for a year.