Leveraging Generative AI for Data-Driven Insights and Visualization in Python






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Leveraging Generative AI for Data-Driven Insights and Visualization in Python

Chitresh Goyal, Neelima Ratra, Swati Singh, Neha Kaushik

Abstract:

In this work, we introduce a novel solution that integrates Python, Streamlit, OpenAI, and embeddings to extract insights and generate visualizations from various data sources. Our approach empowers users to interact with data in plain text, enabling a more intuitive and efficient data analysis process. By leveraging Generative AI, our system not only simplifies data exploration but also addresses the challenges of identifying and generating charts, making data visualization more accessible. The solution accommodates diverse data sources, including PostgreSQL and CSV files, while ensuring a secure and user-friendly experience. This paper aims to demonstrate the effectiveness of combining unsupervised and supervised learning algorithms in real-time text analysis, providing a smart, quick, and scalable method for data-driven decision-making.

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