Predictive Analytics: Predicting Sales & Customer Lifetime Value

In recent years retailing has changed from a fragmented space into a winner-takes-all sector in which a key differentiating factor is the ability to tightly predict demand and measure customer lifetime value. Begin this course by attempting to predict the sales for each week in a Walmart store. You will explore and visualize your data creating an Azure machine learning workspace and a hosted Python notebook to write code. Then perform regression analysis to predict the sales after one-hot encoding the requisite explanatory variables. You will apply different models as well including ridge regression K-nearest neighbors decision trees random forests and extra tree regressors. Next predict the customer lifetime value using regression analysis and perform cross-validation and feature selection on the model in order to improve its performance. Finally experiment with feature selection including recursive feature elimination lasso regularization and linear SVR. ?