This chapter was fundamental in helping you prepare a dataset for machine learning with scikit-learn. You have learned about the constraints that are imposed when you do machine learning with scikit-learn and how to create a dataset that is perfect for scikit-learn.
You have also learned how the k-NN algorithm works behind the scenes and have implemented a version of it using scikit-learn to predict whether a transaction was fraudulent. You then learned how to optimize the parameters of the algorithm using the popular GridSearchCV algorithm. Finally, you have learnt how to standardize and scale your data in order to optimize the performance of your model.
In the next chapter, you will learn how to classify fraudulent transactions yet again with a new algorithm – the logistic regression algorithm!
