🤖 Offline Smart Data Normalizer (AI-Inspired Project)

A Streamlit web app that automatically detects dataset type (like Employee, Car, or Student data) and normalizes numeric columns using Python, Pandas, and Scikit-Learn — all offline and free.

💡 Originally designed to work with OpenAI / Google Gemini APIs, but now optimized for offline use — no API key or internet required!

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🚀 Features

• 📤 Upload CSV or Excel files
  Supports .csv and .xlsx formats up to 200MB.

• 🧠 Automatic Dataset Type Detection (Offline)
  The app smartly detects dataset type (Employee, Student, Car, etc.) using column names.

• ⚙️ Data Normalization

  • Min-Max Normalization
  • Standard (Z-Score) Normalization

• 📊 Live Data Preview
  View your original and normalized data instantly.

• 📥 Download Normalized File
  Export normalized data in both CSV and Excel formats.

• 💾 Offline & Free
  100% local — no API calls, no cost, no rate limits.

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🧰 Technologies Used

Technology	Purpose
🐍 Python 3.10+	Core programming language
📊 Pandas	Data handling & cleaning
🧮 Scikit-Learn	Data normalization (MinMaxScaler, StandardScaler)
📘 OpenPyXL	Excel file support
🌐 Streamlit	Interactive web UI
🧠 (Optional) Gemini / OpenAI API	For future AI dataset detection

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⚙️ How to Run Locally

1️⃣ Clone the repository

git clone https://github.com/ZohaiAli/offline-data-normalizer.git
cd offline-data-normalizer