Offered By: IBMSkillsNetwork
Build Your Spending Insights Advisor with LLM
Make your transaction records smarter! This hands-on project integrates Large Language Models (LLMs) with a credit card transaction database using LangChain's SQLChain. You will develop an AI-assisted tool that enables effortless querying in natural language and offers immediate and valuable insights into your spending habits.
Continue readingGuided Project
Artificial Intelligence
159 Enrolled4.3
At a Glance
Make your transaction records smarter! This hands-on project integrates Large Language Models (LLMs) with a credit card transaction database using LangChain's SQLChain. You will develop an AI-assisted tool that enables effortless querying in natural language and offers immediate and valuable insights into your spending habits.
Imagine engaging in a casual conversation with your transaction records, effortlessly inquiring about your spending habits and receiving immediate, insightful responses. This scenario is not a futuristic fantasy but a present reality made possible by our innovative project. In this tutorial, we leverage the capabilities of LangChain's SQLChain to seamlessly connect a credit card transaction database with Large Language Models (LLMs). Our goal is to enable intuitive, natural language querying, offering you instant and profound insights into your financial behaviour. Welcome to a new era of financial management where complex queries are transformed into simple, conversational interactions.
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Demo
👉 Check out the example app you'll create.
Demo
👉 Check out the example app you'll create.A Look at the Project Ahead
Here's what you will learn to:
- Integrate LLMs with SQL databases to handle data queries, enhancing your skills in database management and working with LLMs.
- Enhance the capabilities of LLMs by using the techniques of prompt engineering.
- Transform any database data into understandable and actionable insights.
What You'll Need
A fundamental understanding of Python is beneficial.Â