In this section, we are going to discuss how to build and evaluate regression models using machine learning algorithms in Python. By the end of this section, we will have built a predictive model using a linear regression algorithm to predict the CLV, more specifically, the expected 3 month customer value. We will be mainly using the pandas, matplotlib, and scikit-learn packages to analyze, visualize, and build machine learning models that predict the expected 3 month customer value. For those readers who would like to use R instead of Python for this exercise, you can skip to the next section.
For this exercise, we will be using one of the publicly available datasets from the UCI Machine Learning Repository, which can be found at this link: http://archive.ics.uci.edu/ml/datasets/online+retail.
You can follow this link and download the...
