The aim of the project is to predict future customer demand for repeat-buying items based on available customer purchase records. However, the purchase history for a single customer may not be sufficient to base predictions on. Also, some purchase records might be missing due to sales events at competitors’ locations. Thus, treating each customer as […]

Workflow management frameworks support the creation of task dependencies and make efficient use of resources while running those workloads. Typically, these tasks can be long running processes like machine learning algorithms or access data from databases. Workflow management consists of mapping tasks to suitable resources and the management of workflow execution in a cloud environment. […]

Artificial intelligence, especially Machine learning algorithms, plays important roles in building recommendation systems and promotional forecasting systems for retailers. However, training a machine learning model requires the choice of a number of significant features and requires tuning a large set of configurations. Therefore, it takes a long time for humans to find the optimal configuration […]

This project uses the purchase history data from loyalty member cards at the basket level (i.e., all items bought by a customer during a particular trip) for customers under the loyalty program of a chain drug store to develop a model that can generate a realistic future “customer shopping list” (i.e., customer baskets) using the […]