NEWSLETTER
LangChain is an open source framework that allows developers to easily create LLM-based applications. It allows you to easily connect LLMs with external data sources to increase the capabilities of these models and achieve better results. The framework is widely used in building chatbots, augmented retrieval generation, and document summarization applications. This article lists the top LangChain books that one should read in 2024 to deepen their understanding of this trending topic.
Quick Start Guide for Large Language Models
This book guides how to work, integrate and implement LLM to solve real-world problems. The book covers the inner workings of LLMs and provides sample code for working with models such as GPT-4, BERT, T5, LLaMA, etc.
<h3 class="wp-block-heading" id="h-introduction-to-generative-ai“>Introduction to Generative ai
“Introduction to Generative ai” covers the fundamentals of generative ai and how to use it safely and effectively. It also provides guidance on how to use this technology in our personal and professional workflows.
<h3 class="wp-block-heading" id="h-generative-ai-with-langchain”>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 rapid engineering to improve performance.
LangChain Crash Course
This is a short book that covers the basics of LangChain. Teaches how to build LLM-based applications using LangChain through hands-on exercises.
LangChain in your pocket
“LangChain in your Pocket” is a guide to building powerful applications using LLM. The book covers topics such as Auto-SQL, NER, RAG, autonomous ai agents, and others. It contains minimal mathematical explanations and step-by-step code explanations with the expected result.
<h3 class="wp-block-heading" id="h-generative-ai-on-aws”>Generative ai on AWS
“Generative ai on AWS” covers the entire lifecycle of the generative ai project on amazon Bedrock. The book covers various models such as Stable Diffusion, Flamingo and IDEFICS. Additionally, it guides how to use frameworks like LangChain to develop agents and actions.
Machine Learning Engineering with Python
This book is a complete guide to building and scaling machine learning projects that solve real-world problems. He covers the different principles of MLOps 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.
Application development with GPT-4 and ChatGPT
This book teaches how to build applications with large language models, such as text generation, question-and-answer, and content summarization tools. The book also covers topics such as rapid engineering, model tuning, and frameworks such as LangChain.
LangChain Manual
This book is a complete guide to integrating and implementing LLM using the LangChain framework. The book covers how to create applications such as chatbots, document analysis, and code analysis.
LangChain for everyone
“LangChain for Everyone” covers the basics of LangChain and how it is used in travel, education, communication, etc. The book covers practical ways the framework can be leveraged to develop LLM-driven applications and helps readers prepare for an ai. -dominated future.
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If you would like to suggest any books that we have missed on this list, please email us at asif@marktechpost.com
Shobha is a data analyst with a proven track record in developing innovative machine learning solutions that drive business value.
