The Interactive Python notebooks can be opened using tools like Jupyter Notebooks or by opening .ipynb files in Github/browser For Python3 Install the required libraries using Pip such as pip install sklearn pip install pandas pip install numpy pip install matplotlib For R Install the required libraries using install.packages or RStudio Run the files using R -f <filename> or Run in RStudio RBF SVM SVM Radial Basis Function RBF Variation with C and Gamma SVM variations with C and Gamma Tuning a linear SVM for Purpose SVC Types Running algorithms to find the best parameters Grid Search Grid Search Principle Component Analysis Plot the data Kaggle Credit Card Fraud True Positive Rate vs False Positive Rate on Credit Card data TPR FPR Precision Recall on Credit Card data Precision Recall Sources 1. Dummy data and practise from Coursera - Machine Learning - University of Michigan 2. Kaggle datasets and competitions Fork this on Github to make changes!
