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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.

GPL-3.0 license

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Name		Name	Last commit message	Last commit date
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Insurance Product Purchase Prediction Abstract.pdf		Insurance Product Purchase Prediction Abstract.pdf
Insurance Product Purchase Prediction.ipynb		Insurance Product Purchase Prediction.ipynb
LICENSE		LICENSE
README.md		README.md

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Insurance-Product-Purchase-Prediction

ML Dataset Analysis

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The ipynb file which contains my analysis
The project abstract that gives you the whole description

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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.

machine-learning data-preprocessing evaluation-metrics decision-tree-regression random-forest-regression cost-prediction neural-network-regression ml-models gradient-boosting-regression insurance-product customer-characteristics product-options

GPL-3.0 license

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