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--- |
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license: mit |
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language: |
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- en |
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metrics: |
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- accuracy |
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- roc_auc |
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- precision |
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- f1 |
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- confusion_matrix |
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base_model: |
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- Gourav18/AutoML |
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new_version: Gourav18/AutoML |
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library_name: sklearn |
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tags: |
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- code |
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- AutoMl |
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--- |
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AutoML |
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# AutoML Application |
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An automated machine learning application built with Streamlit that helps users to: |
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- Load and preprocess data |
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- Train multiple ML models (Logistic Regression, SVM, Random Forest) |
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- Automatically select the best model |
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- Visualize model performance |
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- Make predictions with the trained model |
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## Features |
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- **Data Upload & Analysis**: Upload CSV or Excel files, view statistics, and visualize correlations |
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- **Automated Data Preprocessing**: Handle missing values and categorical encoding |
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- **Model Training**: Train multiple models with hyperparameter tuning |
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- **Model Visualization**: Compare model performance with various metrics |
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- **Prediction**: Make predictions using the trained model |
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## Setup |
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1. Clone this repository |
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2. Install the requirements: |
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``` |
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pip install -r requirements.txt |
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``` |
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3. Run the application: |
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``` |
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streamlit run main.py |
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``` |
