What do you think?
Rate this book
Building LLMs for Production: Enhancing LLM Abilities and Reliability with Prompting, Fine-Tuning, and RAG
- GenresArtificial Intelligence
679 pages, Kindle Edition
Published May 5, 2024
215 people are currently reading
42 people want to read
About the author
Louis-François Bouchard
3 books9 followersLouis-François Bouchard is from Montréal, Canada, and is known as What's AI on YouTube.
He focuses on making AI accessible by sharing and explaining it in simple terms, sharing the new research state and applications for everyone, demystifying the AI “black box” for everyone, and sensitizing people about the risks of using it.
Louis-François recently dropped out of his Ph.D. at Mila/Polytechnique Montréal to focus on his love of education on YouTube and as a co-founder and CTO at Towards AI. He aims to build an industry-relevant skillset for working with AI and popularizing the field.
He focuses on making AI accessible by sharing and explaining it in simple terms, sharing the new research state and applications for everyone, demystifying the AI “black box” for everyone, and sensitizing people about the risks of using it.
Louis-François recently dropped out of his Ph.D. at Mila/Polytechnique Montréal to focus on his love of education on YouTube and as a co-founder and CTO at Towards AI. He aims to build an industry-relevant skillset for working with AI and popularizing the field.
Ratings & Reviews
Friends & Following
Create a free account to discover what your friends think of this book!
Community Reviews
Displaying 1 - 2 of 2 reviews
December 30, 2024
In the rapidly evolving landscape of Generative AI, Building LLMs for Production offers a comprehensive foundation for creating production-grade LLM applications.
I especially liked the book's well-structured organization. It starts with introductory material that gradually builds up to cover the current generation of LLMs, prompt engineering, retrieval-augmented generation (RAGs), and fine-tuning. This logical progression makes it accessible and easy to follow.
Given the sheer volume of new material emerging daily, staying updated on developments in the field is overwhelming. This book highlights references to pivotal papers and advancements, providing invaluable context for understanding key concepts.
The supplementary material further enhances the learning experience. Thoughtfully crafted, it reinforces the book's content and serves as an excellent starting point for putting the discussed concepts into practice.
I especially liked the book's well-structured organization. It starts with introductory material that gradually builds up to cover the current generation of LLMs, prompt engineering, retrieval-augmented generation (RAGs), and fine-tuning. This logical progression makes it accessible and easy to follow.
Given the sheer volume of new material emerging daily, staying updated on developments in the field is overwhelming. This book highlights references to pivotal papers and advancements, providing invaluable context for understanding key concepts.
The supplementary material further enhances the learning experience. Thoughtfully crafted, it reinforces the book's content and serves as an excellent starting point for putting the discussed concepts into practice.
February 24, 2025
Wow!
i feel lucky to have found. this book and all the resources it links to —this book covers everything and offers countless free resources to practice what you learn and to go more in depth on topics that you want to get more education on
i feel lucky to have found. this book and all the resources it links to —this book covers everything and offers countless free resources to practice what you learn and to go more in depth on topics that you want to get more education on
Displaying 1 - 2 of 2 reviews