This is part two of the multi part series where we will build a Modelshop model from scratch. You can find the first part, here. In this video, we will build on the exploratory analysis we performed last time and use machine learning to determine the important features, weights, and cut offs for optimally predicting churn. We will also learn how to deploy that ML model and extract predictions along with confidence levels. Best of all we won’t have to write any code!
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The End of “As Low As” Credit Offers
For decades, credit marketing has relied on a frustratingly vague model. We’ve all seen it: solicitations for “rates as low
August 21, 2025
