Linear Regression Web App is an implementaion of linear regression in python from scratch using Gradient Descent Algorithm and Adaptive Epochs. The web app features options to generate random dataset or to upload one.
- Generate or Upload dataset.
- Plots scatter plot from dataset.
- Trains based on Adaptive Epoch and Gradient Descent Algorithm.
- Shows live improvement in loss.
- Shows predicted Slope and Intercept of regression line.
- Plots the regression line and learning curve.
- Generates a GIF of improvement in regression line.
- Clone the repo or download manually.
git clone https://github.com/shubhayu-64/Linear_regression_webapp.git
- Move to the directory
cd Linear_regression_webapp - Use pip to install requirements.
pip install -r requirements.txt
- Run the web app from terminal.
streamlit run main.py
- Choose to generate or upload dataset.
- Set Intercept Priority parameter and Learning Rate limit.
- The rest is very intuitive.
- Trining quits very fast? Maybe the dataset doesn't have Linear relationship.
- Have any suggestion for a feature? Feel free to raise an issue.
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. Please make sure to update tests as appropriate.
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Made with ❤️ and Python