Ebooks

Building LLMs for Production: Enhancing LLM Abilities and Reliability with Prompting, Fine-Tuning, and RAG


Building LLMs for Production: Enhancing LLM Abilities and Reliability with Prompting, Fine-Tuning, and RAG
Building LLMs for Production: Enhancing LLM Abilities and Reliability with Prompting, Fine-Tuning, and RAG

English | 2024 | ISBN : 979-8327302143 | 475 pages| True EPUB | 11.12 MB

“This is the most comprehensive textbook to date on building LLM applications – all essential topics in an AI Engineer’s toolkit.”
– Jerry Liu, Co-founder and CEO of LlamaIndex

TL;DR
With amazing feedback from industry leaders, this book is an end-to-end resource for anyone looking to enhance their skills or dive into the world of AI and develop their understanding of Generative AI and Large Language Models (LLMs). It explores various methods to adapt “foundational” LLMs to specific use cases with enhanced accuracy, reliability, and scalability. Written by over 10 people on our Team at Towards AI and curated by experts from Activeloop, LlamaIndex, Mila, and more, it is a roadmap to the tech stack of the future.
The book aims to guide developers through creating LLM products ready for production, leveraging the potential of AI across various industries. It is tailored for readers with an intermediate knowledge of Python.

[/b]What’s Inside this 470-page Book?
Hands-on Guide on LLMs, Prompting, Retrieval Augmented Generation (RAG) & Fine-tuning
Roadmap for Building Production-Ready Applications using LLMs
Fundamentals of LLM Theory
Simple-to-Advanced LLM Techniques & Frameworks
Code Projects with Real-World Applications
Colab Notebooks that you can run right away
Community access and our own AI Tutor

Table of Contents
Chapter I Introduction to Large Language Models
Chapter II LLM Architectures & Landscape
Chapter III LLMs in Practice
Chapter IV Introduction to Prompting
Chapter V Introduction to LangChain & LlamaIndex
Chapter VI Prompting with LangChain
Chapter VII Retrieval-Augmented Generation
Chapter VIII Advanced RAG
Chapter IX Agents
Chapter X Fine-Tuning
Chapter XI Deployment

[b]What Experts Think About The Book
“A truly wonderful resource that develops understanding of LLMs from the ground up, from theory to code and modern frameworks. Grounds your knowledge in research trends and frameworks that develop your intuition around what’s coming. Highly recommend.”
– Pete Huang, Co-founder of The Neuron
“This book is filled with end-to-end explanations, examples, and comprehensive details. Louis and the Towards AI team have written an essential read for developers who want to expand their AI expertise and apply it to real-world challenges, making it a valuable addition to both personal and professional libraries.”
– Alex Volkov, AI Evangelist at Weights & Biases and Host of ThursdAI news
“This book is the most thorough overview of LLMs I’ve come across. An excellent primer for newcomers and a valuable reference for experienced practitioners.”
– Shaw Talebi, Founder of The Data Entrepreneurs, AI Educator and Advisor
Whether you’re looking to enhance your skills or dive into the world of AI for the first time as a programmer or software student, our book is for you. From the basics of LLMs to mastering fine-tuning and RAG for scalable, reliable AI applications, we guide you every step of the way.

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