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LangChain Crash Course

Build OpenAI LLM powered Apps: Fast track to building OpenAI LLM powered Apps using Python

Greg Lim

$25.95   $23.75

Paperback

Not in-store but you can order this
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English
Greg Lim
20 September 2024
In this short course, we take you on a fun, hands-on and pragmatic journey to learn how to build LLM powered apps using LangChain. You'll start building your first Generative AI app within minutes. Every section is recorded in a bite-sized manner and straight to the point as I don't want to waste your time (and most certainly mine) on the content you don't need.

The goal of this course is to teach you LangChain development in a manageable way without overwhelming you. We focus only on the essentials and cover the material in a hands-on practice manner for you to code along.

Working Through This Course

This course is purposely broken down into short sections where the development process of each section will center on different essential topics. The course a practical hands on approach to learning through practice. You learn best when you code along with the examples.
By:  
Imprint:   Greg Lim
Dimensions:   Height: 235mm,  Width: 191mm,  Spine: 5mm
Weight:   168g
ISBN:   9789819411474
ISBN 10:   9819411475
Pages:   88
Publication Date:  
Audience:   General/trade ,  ELT Advanced
Format:   Paperback
Publisher's Status:   Active

Reviews for LangChain Crash Course: Build OpenAI LLM powered Apps: Fast track to building OpenAI LLM powered Apps using Python

""I found this book answered a lot of questions for me on how AI and LLM apps work. By building simple practical apps like chatting with a document using the Langchain framework and getting assistance on writing articles, one learns the features of the framework quickly! This book is written in a simple step-by-step fashion to enable you to learn quickly and stick to the point. The practical examples are great for learning"" Arnold Graaff ""This book gave me a quick intro into lanchain use with LLMs. In just a few hours, everything is set up and running, and you get a good feel for the libraries and potentials of LLM with LangChain."" Morten Wagner


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