AquaLearn is a powerful and user-friendly AutoML application built with Streamlit and H2O.ai. It allows users to easily upload datasets, train machine learning models, and make predictions, all through an intuitive web interface.
- CSV File Upload: Easy data import with preview functionality
- Automatic Feature Preparation: Streamlined data preprocessing
- AutoML: Customizable algorithms and parameters for optimal model selection
- Model Performance Visualization: Clear insights into model performance
- Model Saving and Downloading: Preserve and share your trained models
- Further Model Training: Refine models with additional training
- Easy Predictions: Make predictions using uploaded models
- Upload your CSV dataset
- Select problem type (Classification or Regression)
- Choose target column and algorithms
- Run AutoML with customizable parameters
- View results, save models, and make predictions
Visit the AquaLearn Hugging Face Space to start using the application immediately.
To run AquaLearn locally:
- Clone the repository
- Install dependencies:
pip install -r requirements.txt - Run the app:
streamlit run app.py
To run AquaLearn using Docker:
- Build the Docker image:
docker build -t aqualearner . - Run the container:
docker run -p 7860:7860 aqualearner
Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the MIT License.