E-Commerce Data Analysis Project 📊🛒

A comprehensive project utilizing a 2.7 billion-parameter Large Language Model (LLM) to analyze both structured and unstructured e-commerce data. This system generates actionable insights visualized through dynamic graphs, including pie charts, bar graphs, and line graphs, to aid in strategic decision-making.

Video Demonstration

Screen.Recording.2025-02-21.174236.1.1.mp4

Other Images

Technologies Used

• Frontend: React.js, Tailwind CSS, D3.js
• Backend: Node.js, Express.js, MongoDB
• Machine Learning: Python, TensorFlow, scikit-learn

Features

• Data Integration: Combines structured data (e.g., sales records) and unstructured data (e.g., customer reviews) for holistic analysis.
• Advanced Analytics: Employs machine learning algorithms to identify trends, customer segmentation, and sales forecasting.
• Dynamic Visualizations: Generates interactive charts and graphs to represent data insights effectively.
• User-Friendly Interface: Provides an intuitive dashboard for users to explore various data insights.