Build an AI-Powered Expense Tracker using FastAPI, Machine Learning, Scikit-Learn, and Tailwind CSS!
In this tutorial, you'll create a smart expense management system that automatically classifies expenses into categories like Food, Transport, Bills, and Cloud Services using Machine Learning. The application features a clean dashboard, real-time expense tracking, and automatic AI-powered categorization.
🔥 Features Included:
✅ AI Expense Classification
✅ Automatic Category Prediction
✅ Smart Expense Dashboard
✅ Real-Time Spending Analytics
✅ Category-wise Expense Breakdown
✅ FastAPI Backend
✅ Scikit-Learn Machine Learning Model
✅ Tailwind CSS Modern UI
✅ Transaction History
✅ Personal Finance Management
🛠 Technologies Used:
• Python
• FastAPI
• Scikit-Learn
• CountVectorizer
• Multinomial Naive Bayes
• Jinja2 Templates
• Tailwind CSS
• HTML5
📚 What You'll Learn:
Build AI-powered finance applications
Train a text classification model
Automatically categorize expenses with Machine Learning
Develop FastAPI web applications
Create modern dashboards with Tailwind CSS
Deploy AI models inside real-world web applications
💡 Project Overview:
Users simply enter an expense title and amount. The trained Machine Learning model analyzes the text and automatically predicts the most appropriate category, making personal finance tracking faster, smarter, and more organized.
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📂 Source Code Available For Members
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