| title: PromptPrepML | |
| emoji: 🤖 | |
| colorFrom: blue | |
| colorTo: indigo | |
| sdk: streamlit | |
| sdk_version: 1.28.0 | |
| python_version: 3.11 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| # PromptPrepML | |
| AI-Powered Machine Learning Data Preprocessing Assistant | |
| Upload your dataset and describe your preprocessing needs in natural language. Our intelligent system will automatically: | |
| - Detect and remove identifier columns | |
| - Extract date features | |
| - Handle categorical encoding | |
| - Scale numeric features | |
| - Generate ML-ready datasets | |
| - Create reusable pipelines | |
| ## 🚀 Features | |
| - **🧠 Intelligent Preprocessing**: Smart column detection and processing | |
| - **📊 Automated EDA**: Comprehensive data analysis reports | |
| - **🔧 Smart Feature Engineering**: Advanced feature extraction | |
| - **⚙️ Reusable Pipelines**: Scikit-learn pipelines for production | |
| - **📂 Clean Outputs**: ML-ready train/test datasets | |
| ## 📋 Usage | |
| 1. Upload your CSV dataset | |
| 2. Describe your preprocessing needs in natural language | |
| 3. Click "Process Dataset" | |
| 4. Download your ML-ready results | |
| ## 🛠️ Tech Stack | |
| - **Backend**: Python, FastAPI, scikit-learn | |
| - **Frontend**: Streamlit | |
| - **EDA**: ydata-profiling | |
| - **ML**: pandas, numpy | |