Quick Start Guide to Large Language Models: Strategies and Best Practices for ChatGPT, Embeddings, Fine-Tuning, and Multimodal AI (Addison-Wesley Data & Analytics Series)

Sinan's writing is exemplar in how practical and guided his step-by-step resources are. Ideal for anyone looking to either start or improve on their use of LLMs in real-world applications.The book covers everything from fine-tuning and prompt engineering to deploying scalable systems, with hands-on examples and clear explanations. It’s ideal for data scientists and developers, but really useful even for the not technically inclined (though you may skip some pages).The inclusion of real, more advanced techniques like retrieval-augmented generation, good evaluation practices, and even building corpuses makes this a must-have for modern AI projects.Highly recommended for anyone building with LLMs!

More chapters, more content, more up to date examples. Worth checking out if you're a beginner to LLMs / AI!

Clear examples, easy to follow, well-written.

Sinan Ozdemir’s Quick Start Guide to Large Language Models is an invaluable resource for anyone diving into the world of LLMs. This book breaks down complex topics with clear, practical steps, covering everything from fine-tuning and prompt engineering to deploying models like GPT-4 and LLaMA in real-world applications. The hands-on exercises and examples make it easy to apply the concepts right away. Perfect for beginners and experienced practitioners alike—highly recommended.

What I love most about this book is how accessible it makes such a complex subject. Even if you don’t have prior experience with LLMs, Sinan walks you through every step, providing clear instructions, practical case studies, and hands-on exercises that make learning both engaging and practical.This guide is perfect for data scientists, AI enthusiasts, and developers. I highly recommend this book to anyone looking to start or deepen their journey into the world of large language models.

The author knows the material and clearly does an excellent job of communicating it, in a way for novices to understand. He steadily builds up the reader's confidence with LLMs. This edition addresses many of the issues of the first edition, including updated models and new chapters. I enthusiastically recommend this book for anyone new to the area.

Useful for those who are new to working with LLMs and want a hands-on guide. The clear instructions and real-world examples make it approachable, especially if you’re looking to apply LLMs to practical projects while diving just deep enough into the technical details.That said, if you’re already an expert with LLMs or are looking for more advanced PhD level concepts, this book might not be for you.

All of a sudden, software developers need to know a lot about LLMs. I found this book useful for getting a technical overview of LLMs, along with tactical ways to apply them. It balances "just enough" information to get you productive in a relatively short book, while still being thorough and technical.