This repository contains a Jupyter notebook file and a python script file that covers using machine learning to predict diabetes and deployment of the model using Streamlit. It covers various topics such as data loading, data preprocessing, model training, model evaluation and deployment.
- Data loading and preprocessing using pandas
- Training and evaluating a machine learning model using scikit-learn
- Deploying the model using Streamlit
To use the notebooks and scripts in this repository, you will need to have a working installation of Python and Jupyter Notebook. You can download the latest version of Python from the official website (https://www.python.org/) and install Jupyter Notebook by running pip install jupyter. You will also need to install the dependencies listed in the requirements.txt file by running pip install -r requirements.txt.
Once you have the necessary software installed, you can clone or download this repository to your local machine. Then, open a terminal or command prompt and navigate to the directory where you downloaded the repository.
The deployed model can be accessed via the link: https://favourogboi-diabetes-prediction-machinelearn-deploymodel-497qhu.streamlit.app/
If you have any suggestions or find any errors, please feel free to open an issue or submit a pull request.