5 Top Large Language Models & Generative AI Books

Master LLMs & Generative AI Through These Five Books

This article reviews five key books that explore the rapidly evolving fields of large language models (LLMs) and generative AI, providing essential insights into these transformative technologies. 

NLP with Transformers introduces readers to transformer architecture for natural language processing, offering practical guidance on using Hugging Face for tasks like text classification. Build a Large Language Model (From Scratch) by Sebastian Raschka provides a comprehensive guide to constructing LLMs, from data preparation to fine-tuning. 

Hands-On Large Language Models by Jay Alammar and Maarten Grootendorst delivers practical tools for Python developers, focusing on applications like semantic search and prompt engineering. Generative AI on AWS by Chris Fregly and team demystifies generative AI integration into business, emphasizing model selection and deployment on AWS. 

LLMs in Production by Christopher Brousseau and Matthew Sharp offers strategies for deploying LLMs in real-world scenarios, highlighting the challenges of scaling AI systems. Together, these books equip practitioners with the knowledge and tools needed to harness the potential of LLMs and generative AI in today’s digital landscape.