An Example of Training and Testing a Machine Learning Model

A machine learning model is built in several phases. After data access and data preparation, we usually partition the data into a training set and a test set for training and evaluating the machine learning model, respectively. There are a number of scoring metrics available for the evaluations, such as accuracy or the Area under the Curve. 

In this video we go through the most common steps required to build and evaluate a machine learning model.