Hands-on large language models, by Jay Alammar and Maarten Grootendorst, is a beginner-friendly guide to understanding and using large language models (LLMs). Designed for readers with some basic knowledge of Python and machine learning, the book breaks down complex ideas into simple, clear explanations with plenty of visuals and examples.

The book has three main parts. The first part explains the basics of how LLMs work, including how they process text, learn patterns, and handle tokens. Concepts like embeddings and attention are explained with helpful diagrams. The second part focuses on practical uses, showing how LLMs can sort text, find patterns, or search for information. The third part looks at advanced topics, like fine-tuning models for specific tasks or combining text with images.

One of the best features of the book is its hands-on approach. Readers can follow along with coding exercises using a platform like Google Colab, making it accessible even without powerful computers. The book also discusses the ethical use of artificial intelligence (AI) and its limitations, helping readers think about the responsible use of this technology.

This book is ideal for programmers, students, or anyone interested in learning about LLMs. With its clear explanations and practical exercises, it provides a great technical introduction to one of the most powerful tools in AI today.

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