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A machine learning project for predicting the chances of having a stroke

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strokesML

A machine learning project for predicting the chances of having a stroke

Code

Instructions

  1. Create a 3.10 python environment
  1. Use the requirements.txt file to install the necessary packages pip install -r requirements.txt. The file is found in the root project folder.
  2. Use your new environment to execute the main.py file. NOTA: Be sure that you execute the file form the root project folder.
  3. Wait until the automated pipeline is executed and the best model is proposed. NOTA: This could take several minutes.

Results

The result is a model predicting a stroke with a 85% accuracy.

Deployment script

The main.py script makes a ML pipeline on the Stroke data set by using sklearn with python.

Jupyter Notebook

The main script contains only the deployment of the ML pipeline, we are going to skip the data analysis part with all its graphics, as it is better to show it in the Jupyter Notebook.

The jupyter notebook with all the logic and analysis followed, can be found in the root/notebook folder.

Data

The strokes data is found in the root/data folder

License

GNU GENERAL PUBLIC LICENSE, see LICENSE file for more information.

About

A machine learning project for predicting the chances of having a stroke

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