After building a machine learning model or maybe a few in usual scenerio, we have one of few metrics to compare the efficiency of the models. It can be Accuracy, AUC, F1 score etc. But even after comparing these scores, it's highly recommended to look for few more results so as to see the performance of model over time. In this repository, I am going to share few Model Performance Analysis steps which I generally take to sure shot that one model into production environment.
Basically we are going to learn about 3 main Performance reports: