LangChain is an open-source framework that allows developers to build LLM-based applications easily. It provides for easily connecting LLMs with external data sources to augment the capabilities of these models and achieve better results. The framework is widely used in building chatbots, retrieval-augmented generation, and document summarization apps. This article lists the top LangChain books one should read in 2024 to deepen one’s understanding of this trending topic.
Quick Start Guide to Large Language Models
This book guides how to work with, integrate, and deploy LLMs to solve real-world problems. The book covers the inner workings of LLMs and provides sample codes for working with models like GPT-4, BERT, T5, LLaMA, etc.
Introduction to Generative AI
“Introduction to Generative AI” covers the fundamentals of generative AI and how to use it safely and effectively. It also guides on how to use this technology in our personal and professional workflows.
Generative AI with LangChain
This book is a guide to using the LangChain framework to develop and deploy production-ready large language model (LLM) applications. It explains the fundamentals of LLMs and generative AI and also covers prompt engineering to improve performance.
LangChain Crash Course
This is a short book covering the fundamentals of LangChain. It teaches how to build LLM-powered applications using LangChain using hands-on exercises.
LangChain in your Pocket
“LangChain in your Pocket” is a guide to creating powerful applications using LLMs. The book covers topics like Auto-SQL, NER, RAG, Autonomous AI agents, and others. It contains minimal mathematical explanations and has step-by-step code explanations with expected output.
Generative AI on AWS
“Generative AI on AWS” covers the entire generative AI project lifecycle on Amazon Bedrock. The book covers various models such as Stable Diffusion, Flamingo, and IDEFICS. Moreover, it guides how to use frameworks like LangChain to develop agents and actions.
Machine Learning Engineering with Python
This book is a comprehensive guide to building and scaling machine-learning projects that solve real-world problems. It covers the different MLOps principles and talks about CI/CD pipelines, system design, and various cloud platforms. The book also includes a section on generative AI and building LLM-powered pipelines using LangChain.
Developing Apps With GPT-4 and ChatGPT
This book teaches how to create applications with large language models, such as text generation, Q&A, and content summarization tools. The book also covers topics like prompt engineering, model fine-tuning, and frameworks like LangChain.
LangChain Handbook
This book is a complete guide to integrating and implementing LLMs using the LangChain framework. The book covers how to create applications like chatbots, document analysis, and code analysis.
LangChain for Everyone
“LangChain for Everyone” covers the fundamentals of LangChain and how it is being used in travel, education, communication, etc. The book covers the practical ways the framework can be leveraged to develop LLM-powered applications and helps the readers prepare for an AI-dominated future.
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Shobha is a data analyst with a proven track record of developing innovative machine-learning solutions that drive business value.
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