A Data Science Machine Learning approach to predict the best candidates to be targeted for a marketing campaign
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Updated
Jan 13, 2021 - Jupyter Notebook
A Data Science Machine Learning approach to predict the best candidates to be targeted for a marketing campaign
In this project we will predict the cost required for a patient depending on his/her health conditions.
This project aims to develop a predictive model estimating insurance coverage costs for customers based on their attributes and product choices. The dataset includes transaction and quote details for policy purchasers. The objective is to predict quoted coverage costs, considering customer traits and 7 customizable product options.
I compare the accuracy of health cost prediction of four regression models: Linear, Lasso, Ridge, and Elastic Net Regression.
Web app using univariate regression to predict the cost of opening a new franchise store.
Predicting medical insurance costs using machine learning in Python.
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