Predicting Purchases with Machine Learning – Video

In her project called “More than Guts,” Galvanize Data Science graduate Deseanae Bluiett uses machine learning to easily provide data driven sales and marketing insights. The focal point is an interactive sales and marketing dashboard that identifies customer segments and utilizes predictive model to predict the likelihood of product purchase. She utilized  machine learning techniques to create and optimize the predictive models in addition to unsupervised learning techniques to create the customer segments.

To create the app interface, she used Flask, Pyxley, Bootstrap, HTML, JAVA, CSS and Python. Though data segmentation and predictive modeling is traditionally applied in business cases, there are plethora of cases where these methods could be beneficial. To illustrate, Deseanae created additional predictive models which alert users when they are entering a potentially dangerous zone based on crime data, gps location and time of day.

Watch her explain her capstone project below:

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