README

This repository was created in order to provide didactical material for the Introduction to Machine Learning for biomedical data analysis in Python course, taught by Dr. Adriano Barbosa-Silva in various Data Science for Health courses.

This repository uses resources collected from diverse sources in the internet. Credits should be given for the authors listed below, from whom I obtained the original material for free code at Kaggle for teaching purposes. They deserve full credits for their great work!

Comparing Classification Models: sklearn iris data, Nilimesh Halder, Accessed Sep. 2019.
Breast Cancer Analysis and Prediction, Vincent Lugat, Accessed Sep. 2019.
Heart diseases predictive model (beginners), Rishabh Pande, Accessed Sep. 2019.
PIMA Indians Diabetes, Rishabh Pande, Accessed Sep. 2019.

To launch the interactive version of such notebooks on-the-fly using the service myBinder, click on the banner below:

Name		Name	Last commit message	Last commit date
Latest commit History 16 Commits
.ipynb_checkpoints		.ipynb_checkpoints
00_Introduction.ipynb		00_Introduction.ipynb
01_Appendix_A_Comparing-different-cross-validation-methods.ipynb		01_Appendix_A_Comparing-different-cross-validation-methods.ipynb
01_Appendix_B_ROC_Curves.ipynb		01_Appendix_B_ROC_Curves.ipynb
01_Appendix_C_plot_all_scaling.ipynb		01_Appendix_C_plot_all_scaling.ipynb
01_Appendix_D_Plot the decision boundaries of a VotingClassifier.ipynb		01_Appendix_D_Plot the decision boundaries of a VotingClassifier.ipynb
01_Appendix_E_Comparison of different linear SVM classifiers on a 2D projection of the iris dataset.ipynb		01_Appendix_E_Comparison of different linear SVM classifiers on a 2D projection of the iris dataset.ipynb
01_Appendix_F - plot_iris_dtc.ipynb		01_Appendix_F - plot_iris_dtc.ipynb
01_Appendix_G_plot_confusion_matrix.ipynb		01_Appendix_G_plot_confusion_matrix.ipynb
01_comparing-classification-models-sklearn-iris-data.ipynb		01_comparing-classification-models-sklearn-iris-data.ipynb
02_Appendix_A_Effect_of_Scaling.ipynb		02_Appendix_A_Effect_of_Scaling.ipynb
02_Appendix_B_Model_Complexity_vs_Accuracy-Copy1.ipynb		02_Appendix_B_Model_Complexity_vs_Accuracy-Copy1.ipynb
02_Appendix_B_Model_Complexity_vs_Accuracy.ipynb		02_Appendix_B_Model_Complexity_vs_Accuracy.ipynb
02_pima-indians-diabetes-beginner.ipynb		02_pima-indians-diabetes-beginner.ipynb
02_pima-indians-diabetes-beginner_MOD_class.ipynb		02_pima-indians-diabetes-beginner_MOD_class.ipynb
03_breast-cancer-analysis-and-prediction.ipynb		03_breast-cancer-analysis-and-prediction.ipynb
04_heart-diseases-predictive-model-beginners.ipynb		04_heart-diseases-predictive-model-beginners.ipynb
04_plot_underfitting_overfitting.ipynb		04_plot_underfitting_overfitting.ipynb
COPYRIGHT.ipynb		COPYRIGHT.ipynb
Iris.csv		Iris.csv
Plotting features importance.ipynb		Plotting features importance.ipynb
README.md		README.md
README.md~		README.md~
Visualizing cross-validation behavior in scikit-learn¶.ipynb		Visualizing cross-validation behavior in scikit-learn¶.ipynb
data-breast-cancer.csv		data-breast-cancer.csv
diabetes.csv		diabetes.csv
heart-disease-data.csv		heart-disease-data.csv
knn_compare_model.png		knn_compare_model.png
model_CART.pickle		model_CART.pickle
model_KNN.pickle		model_KNN.pickle
model_LDA.pickle		model_LDA.pickle
model_LR.pickle		model_LR.pickle
model_NB.pickle		model_NB.pickle
model_SVM.pickle		model_SVM.pickle
plot_unveil_tree_structure.ipynb		plot_unveil_tree_structure.ipynb

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