Integrating LangChain with Amazon SageMaker: A Step-by-Step Guide to Building, Training, and Deploying Large Language Models is a comprehensive guide for data scientists and ML engineers who want to build and deploy state-of-the-art LLMs using LangChain and Amazon SageMaker.This book will teach you how to:

• Get started with LangChain and Amazon SageMaker

• Build and train LLMs for a variety of tasks, including text generation, translation, and question answering
• Deploy your LLMs to production using Amazon SageMaker’s real-time inference endpoints

This book will save you months of time and effort by providing you with a step-by-step guide to building and deploying LLMs using LangChain and Amazon SageMaker.
About the technology
LangChain is a powerful framework for building and deploying LLM-powered applications. It provides a high-level API that makes it easy to interact with LLMs, and it integrates seamlessly with Amazon SageMaker. Amazon SageMaker is a managed machine learning service that makes it easy to build, train, and deploy ML models in the cloud. It provides a wide range of pre-trained models, as well as the tools and infrastructure you need to build and train your own models.
What’s inside
Integrating LangChain with Amazon SageMaker: A Step-by-Step Guide to Building, Training, and Deploying Large Language Models covers everything you need to know to build and deploy LLMs using LangChain and Amazon SageMaker. You’ll learn about the following:

• The basics of LangChain and Amazon SageMaker
• How to build and train LLMs for a variety of tasks

• How to deploy your LLMs to production using Amazon SageMaker’s real-time inference endpoints
• Advanced techniques for building and deploying LLMs, such as using custom content handlers and integrating with other AWS services

About the reader
This book is for data scientists and ML engineers who want to learn how to build and deploy LLMs using LangChain and Amazon SageMaker. You should have a basic understanding of machine learning and Python programming.
LLMs are a rapidly evolving field, and new advances are being made all the time. If you want to stay ahead of the curve and learn how to build and deploy state-of-the-art LLMs, then this book is for you.