Build an LLM Application (from Scratch) (MEAP V03)

In Build an LLM Application (from Scratch), you'll learn to create applications powered by large language models (LLM) from the ground up. In this practical book, you'll build several fully functioning, real-world AI tools-including a search engine, semantic caching for RAG, and autonomous AI agents.
In Build an LLM Application (from Scratch), you'll learn how to
Design and implement efficient search algorithms for LLM applications
Develop custom Retrieval Augmented Generation (RAG) systems
Master deep customization techniques for every aspect of search and RAG components
Understand and overcome the limitations of popular LLM frameworks
Create end-to-end LLM solutions by integrating multiple components cohesively
Apply advanced fine-tuning techniques for task-specific models and domain adaptation
Deploy quantized versions of open-source LLMs using vLLMs and Ollama
Build an LLM Application (from Scratch) shows you just how customizable LLM applications can be when you create your own without using opinionated tools like LangChain and LlamaIndex. You'll learn the fundamentals of AI development hands-on, all without any proprietary tools. Soon you'll have the skills you need to build LLM applications, tailor them to your specific needs, and ensure you have control over your entire system.
about the book
Build an LLM Application (from Scratch) is a practical and comprehensive handbook for creating custom LLM applications without relying on premade frameworks. Its focus on the application layer makes it an ideal companion to Sebastian Raschka's Build a Large Language Model (From Scratch), which takes the same first-principles approach to creating the models themselves. You'll start by mastering the fundamentals of search systems and RAG. Then you'll apply this knowledge to real-world projects, including building a hotel search engine using TripAdvisor review data, implementing semantic caching in RAG production systems, and deploying a full RAG application using Hugging Face and Gradio. By the end of the book, you'll have the skills to build AI agents from scratch, deploy open source LLMs with advanced quantization techniques, and create innovative, specialized LLM applications designed for your specific needs.

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