Breast Cancer Predictor with Scikit Learn, Streamlit and Deployed with Flask and AWS

Binary Classificator Breast Cancer Model with Scikit Learn, Streamlit, Flask and AWS

The Model was trained with Tabular Breast Cancer Data and with the Logistic Regression Scikit-Learn Architecture. The Model predicts if a given cell is either Benign or Malignant, also the U.I. to select the parameters of the cell was built with Streamlit and the API with Flask. Last, the Flask API was deployed on AWS EC2.

Check-it out

Test it by running the app.py file, built with Streamlit, and the api.py file with Flask. Remember first to run the api.py file, copy the http url and saved in the API variable of the app.py file.

Run

python3 api.py

streamlit run app.py

Resources

• Breast Cancer Dataset: https://www.kaggle.com/datasets/uciml/breast-cancer-wisconsin-data
• Breast Cancer Predictor Preview: https://www.youtube.com/watch?v=OaPK7luz-4M