💸 Expenzy: An AI-Powered Expense Tracker with Forecasting, Clustering & Anomaly Detection

Expenzy: A Smart Expense Tracker Built with the MERN Stack and Real Machine Learning

Hey dev community 👋,

I’m excited to share Expenzy — my college mini project that grew into a full-featured personal expense manager built on the MERN stack — with integrated Machine Learning for smarter budgeting!

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🚀 What is Expenzy?

Most expense trackers just record numbers. Expenzy goes beyond that. It helps you:

✅ Log and track expenses securely (with authentication)

✅ Visualize your spending on an intuitive dashboard

✅ Forecast future expenses using Prophet

✅ Detect unusual transactions with Anomaly Detection

✅ Cluster your spending patterns with K-Means Clustering

✅ Predict sales with Logistic Regression

✅ Get personalized budget recommendations — all powered by real ML models!

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⚙️ Tech Stack

• Frontend: React.js (interactive, responsive UI)
• Backend: Node.js + Express.js (API and server logic)
• Database: MongoDB (secure, flexible data storage)
• Machine Learning: Implemented using JS libraries and integrated directly in the backend logic.

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🔑 Why Expenzy is Different

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📊 Key ML Features

📈 Forecasting with Prophet

Predict your future expenses based on historical data so you can plan ahead confidently.

🕵️ Anomaly Detection

Catch suspicious or unusual spending patterns to avoid surprises.

📑 K-Means Clustering

Automatically group your spending categories for clearer insights into your habits.

🎯 Budget Recommendation

Get smart, personalized suggestions on how much to budget based on your spending history.

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🖥️ Live Demo

👉https://expenzy-git-main-bharath-ds-projects.vercel.app

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📂 Source Code

Here’s the complete codebase if you want to explore, fork, or contribute:

👉 Bharath80988/Expenzy

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📌 Why I Built Expenzy

I wanted to challenge myself to:

• Combine a clean MERN architecture with actual Machine Learning models
• Make personal finance smarter, not just a digital ledger
• Learn to deploy full-stack apps with modern tooling

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🚀 What’s Next

✅ Add notifications & alerts for anomalies

✅ Fine-tune ML models with larger datasets

✅ Build a mobile app version for on-the-go tracking

✅ Deploy a robust production version with CI/CD

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🤝 Let’s Connect!

Your feedback is super valuable. Let me know what you think or how you’d improve it!

📫 LinkedIn

⭐️ GitHub

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If you liked this project, please leave a ❤️, star the repo, and share your thoughts below! 🚀✨

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#mernstack #react #node #mongodb #machinelearning #webdev #opensource #budgeting