Tags
Language
Tags
May 2025
Su Mo Tu We Th Fr Sa
27 28 29 30 1 2 3
4 5 6 7 8 9 10
11 12 13 14 15 16 17
18 19 20 21 22 23 24
25 26 27 28 29 30 31
    Attention❗ To save your time, in order to download anything on this site, you must be registered 👉 HERE. If you do not have a registration yet, it is better to do it right away. ✌

    ( • )( • ) ( ͡⚆ ͜ʖ ͡⚆ ) (‿ˠ‿)
    SpicyMags.xyz

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

    Posted By: naag
    Building LLMs for Production: Enhancing LLM Abilities and Reliability with Prompting, Fine-Tuning, and RAG (Updated)

    Building LLMs for Production: Enhancing LLM Abilities and Reliability with Prompting, Fine-Tuning, and RAG
    English | 2024 | ISBN: B0D3G58GDD | Pages: 679 | Epub | 4.20 MB


    TL;DR
    (UPDATED ON OCTOBER 2024) 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.


    What's Inside this 470-page Book? (Updated on October 2024)

    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 Retrieval-Augmented Generation
    Chapter VI Introduction to LangChain & LlamaIndex
    Chapter VII Prompting with LangChain
    Chapter VIII Indexes, Retrievers, and Data Preparation
    Chapter IX Advanced RAG
    Chapter X Agents
    Chapter XI Fine-Tuning
    Chapter XII Deployment

    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.