Build an AI-Powered Inventory Management System using FastAPI, Machine Learning, Scikit-Learn, and Tailwind CSS!
In this project, we create a smart inventory dashboard that analyzes historical sales data and predicts future product demand using Linear Regression. The system automatically identifies products that need restocking and provides real-time inventory insights through a modern web interface.
🔥 Features Included:
✅ AI Demand Forecasting
✅ Inventory Management Dashboard
✅ Product Stock Tracking
✅ Restock Recommendations
✅ FastAPI Backend
✅ Scikit-Learn Machine Learning Model
✅ Tailwind CSS Modern UI
✅ Add New Products
✅ Update Inventory Levels
✅ Sales Trend Analysis
🛠 Technologies Used:
• Python
• FastAPI
• Scikit-Learn
• NumPy
• Linear Regression
• Jinja2 Templates
• Tailwind CSS
• HTML5
📚 What You'll Learn:
How to build AI-powered business applications
Demand forecasting using machine learning
Creating FastAPI web applications
Building modern dashboards
Managing inventory with predictive analytics
Deploying ML models in real-world projects
💡 Project Idea:
This system predicts future product demand based on previous sales history. If predicted demand exceeds current stock levels, the AI automatically flags the product for restocking, helping businesses avoid stock shortages and improve inventory planning.
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📌 Source Code Available For Members
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