This repository contains a case study exploring the development of a Data Science Assistant powered by Large Language Models (LLMs) and the LangChain framework.
The primary objective of this project is to create a Generative AI solution that automates some tasks in Data Analysis, Database Querying, and Retrieval-Augmented Generation. This is achieved by enabling LLM to interpret natural language commands and generate the necessary code to execute these tasks.
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Natural Language to Code Conversion: Transform user requests into executable code for data operations.
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Automated Data Analysis: Streamline various data analysis workflows.
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Database Interaction: Query relational databases using natural language commands.
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Retrieval-Augmented Generation: Enhance LLM capabilities by integrating external data retrieval.
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Time Savings: Automates repetitive coding tasks in data science.
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Improved Accuracy: Reduces human error in code generation.
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Increased Accessibility: Empowers users without extensive coding knowledge to perform data analysis.