Building LLMs for Production e-book is now available at $59.99 $29.99!
What's Inside this 470-page Book (Updated October 2024)?
Please note: this e-book is an interactive resource, not a downloadable PDF.
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Hands-on Guide on LLMs, Prompting, Retrieval Augmented Generation (RAG) & Fine-tuning
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Roadmap for Building Production-Ready Applications using LLMs
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Fundamentals of LLM Theory
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Simple-to-Advanced LLM Techniques & Frameworks
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Code Projects with Real-World Applications
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Colab Notebooks that you can run right away
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Community access and our own AI Tutor
Industry Leaders on the Book
“This is the most comprehensive textbook to date on building LLM applications, and helps learners understand everything from fundamentals to the simple-to-advanced building blocks of constructing LLM applications. The application topics include prompting, RAG, agents, fine-tuning, and deployment - all essential topics in an AI Engineer's toolkit.”
![](https://import.cdn.thinkific.com/909819%2Fcustom_site_themes%2Fid%2FUkMP7r0LQQOR15xQTTIA_Jerry%20Liu.jpeg)
“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.”
![](https://import.cdn.thinkific.com/909819%2Fcustom_site_themes%2Fid%2FTWmKj8bSJmBy2L9tzsiw_Pete%20Huang.jpeg)
“An indispensable guide for anyone venturing into the world of large language models...Covering everything from theory to practical deployment, it’s a must-have in the library of every aspiring and seasoned AI professional.”
![](https://import.cdn.thinkific.com/909819%2Fcustom_site_themes%2Fid%2F1Py4xEXDQ9qzljus99dr_Shashank.jpeg)
“It contains thorough explanations and code for you to start using and deploying LLMs, as well as optimizing their performance. Very highly recommended!”
![](https://import.cdn.thinkific.com/909819%2Fcustom_site_themes%2Fid%2FhfNOGWW3Sp6OCjzDscRn_Luis%20Serrano.jpeg)
“It covers the foundational aspects of LLMs as well as advanced use-cases like finetuning LLMs, Retrieval Augmented Generation and Agents. This will be valuable to anyone looking to dive into the field quickly and efficiently.”
![](https://import.cdn.thinkific.com/909819%2Fcustom_site_themes%2Fid%2F7IYuVoXYSuyTPewuKq0W_Jeremy%20Pinto.jpeg)
Chapter Overview
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Table of Contents
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About The Book
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Introduction
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Why Prompt Engineering, Fine-Tuning, and RAG?
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Coding Environment and Packages
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A Brief History of Language Models
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What are Large Language Models?
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Building Blocks of LLMs
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Tutorial: Translation with LLMs (GPT-3.5 API)
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Tutorial: Control LLMs Output with Few-Shot Learning
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Recap
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Understanding Transformers
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Transformer Model’s Design Choices
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Transformer Architecture Optimization Techniques
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The Generative Pre-trained Transformer (GPT) Architecture
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Introduction to Large Multimodal Models
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Proprietary vs. Open Models vs. Open-Source Language Models
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Applications and Use-Cases of LLMs
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Recap
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Understanding Hallucinations and Bias
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Reducing Hallucinations by Controlling LLM Outputs
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Evaluating LLM Performance
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Recap
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Prompting and Prompt Engineering
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Prompting Techniques
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Prompt Injection and Security
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Recap
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![](https://import.cdn.thinkific.com/909819/YTd5YEtlQJaf8KyREwfv_5.png)
Who is it for?
- $29.99
- AI Practitioners & Programmers Tinkerers
- AI/ML Engineers & Computer Science Professionals
- Students/Researchers & Job Seekers
The Only AI Engineering Toolkit You Need!
To build scalable and reliable products with LLMs
LLM Fundamentals, Architecture, & LLMs in Practice
Foundations
- Building blocks of LLMs: language modeling, tokenization, embeddings, emergent abilities, scaling laws, context size…
- Transformer Architecture: attention mechanism, design choices, encoder-only transformers, decoder-only transformers, encoder-decoder transformers, GPT Architecture, Masked Self-Attention, MinGPT
LLMs in Practice
- Hallucinations & Biases: Mitigation strategies, controlling LLM outputs
- Decoding methods: greedy search, sampling, beam search, top-k sampling, top-p sampling
- Objective functions and evaluation metrics: perplexity metric and GLUE, SuperGLUE, BIG-Bench, HELM, FLASK Benchmarks…
Prompting & Frameworks
Prompting
- Prompting techniques: zero-shot, in context, few-shot, role, chains, and chain-of-thought…
- Prompt Injection and Prompt Hacking
Frameworks
- LangChain: prompt templates, output parsers, summarization chain, QA chains
- LlamaIndex: vector stores, embeddings, data connectors, nodes, indexes
RAG & Fine-Tuning
Retrieval-Augmented Generation Components
- Data Ingestion(PDFs, web pages, Google Drive), text splitters, LangChain Chains
- Embeddings, Vector Stores with Activeloop's Deep Lake
- Querying in LlamaIndex: query construction, expansion, transformation, splitting, customizing a retriever engine…
- Reranking Documents: recursive, small-to-big
- RAG Metrics: Mean Reciprocal Rank (MRR), Hit Rate, Mean Average Precision (MAP), and Normalized Discounted Cumulative Gain (NDCG)...
- Evaluation Tools: evaluating with ragas, custom evaluation of RAG pipelines
Fine-Tuning Optimization Techniques
- LoRA, QLoRA, supervised fine-tuning, SFT RLHF
Agents, Optimization & Deployment
Agents
- Using AutoGPT & BabyAGI with LangChain
- Agent Simulation Project: CAMEL, Generative Agents
- Building Agents, LangGPT, OpenAI Assistants
Optimization & Deployment
- Challenges, quantization, pruning, distillation, cloud deployment, CPU and GPU optimization & deployment, creating APIs from open-source LLMs
More Towards AI's Book Readers' Reviews
Comprehensive Coverage and Practical
Priyankar Kumar
The book has great coverage of nearly all the important topics related to LLMs and application-building with LLMs. I also liked the focus on the hands-on projects, so that you are not just reading but also trying things out.
The book has great coverage of nearly all the important topics related to LLMs and application-building with LLMs. I also liked the focus on the hands-on projects, so that you are not just reading but also trying things out.
Read LessSimply a must-read
Eugenio Galioto
The second version of this book can easily be considered a must-read as well as the first version. It's great to have key and evolving concepts explained like this!
The second version of this book can easily be considered a must-read as well as the first version. It's great to have key and evolving concepts explained like this!
Read LessBest book on the topic
Hiroto Matsushima
FAQ
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What skills do I learn?
The book is packed with theories, concepts, projects, applications, and experience that you can confidently put on your CVs. You can add these skills straight into your resume: Large Language Models (LLMs) | LangChain | LlamaIndex | Vector databases | RAG | Prompting | Fine-tuning | Agents | Deployment & Deployment Optimizations | Creating chatbots | Chat with PDFs | Summarization | AI Assistants | RLHF
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What are the prerequisites to read the book?
The is written for readers without prior knowledge of AI or NLP. It introduces topics from the ground up, aiming to help you feel comfortable using the power of AI in your next project or to elevate your current project to the next level. A basic understanding of Python helps comprehend the code and implementations, while advanced use cases of the coding techniques are explained in detail in the course.
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How do we make sure the book is not outdated?
We ensure the book remains relevant by focusing on the core principles of building production products with LLMs, which are foundational and transferable across generations of models. While the field is fast-evolving and new techniques will emerge, today's LLM developer stack will still be crucial for adapting future models to specific industries and data. Additionally, we provide access to an up-to-date webpage with extra content, code, notebooks, and resources, ensuring readers stay current with the latest advancements.
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Does it come with a physical copy?
No. This e-book version is hosted on the platform (not a pdf). You can purchase a soft or hard copy of the book on Amazon (https://amzn.to/4bqYU9b). If you have a physical copy, email Louis-François at [email protected], and we'd be happy to give you a discount on the e-book!
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Do you have a referral or affiliate program?
If you refer three or more people, we’ll send you a physical copy of our book as a thank you! Additionally, we have an affiliate program for individuals with an audience. By joining, you can earn commissions for every successful referral made through your unique affiliate link. Please email Louis-François at [email protected] with proof of referral.
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Can I take this course within my company?
Yes! We offer both course bundles and custom training solutions tailored specifically for companies. For more information on company packages or to discuss a customized training plan, reach out to Louis at [email protected].