Project for insurance churn prediction with xgboost classification algorithm
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Updated
Nov 6, 2022 - HTML
Project for insurance churn prediction with xgboost classification algorithm
In this analysis, the credit risk dataset consisting of 32851 loan records to determine how best to predict whether or not a loan applicant will repay.
👨🏼⚕️🧠 Web-App predicting brain drain in AI research at public institutions
This research goal is to build binary classifier model which are able to separate fraud transactions from non-fraud transactions.
Creating SQL databases and writing queries in R.
Modelling and prediction of default + deployment via AWS Sagemaker
The goal of this project is to create a classifier and see how accurately it can predict song genres. Taking a dataset from Spotify [Pandya, 2022], which is al- ready using machine learning algorithms for these purposes, can help assess if the resulting model can be considered apt for a large-scale business.
Predicting the probability of a loan applicant paying back the loan.This repository aims to analyze data from different types of personal loans and apply machine learning algorithms to develop a credit risk predictor.
Predict and prevent customer churn in the telecom industry with this project. Harness the power of advanced analytics and Machine Learning on a diverse dataset to develop a robust classification model. Gain deep insights into customer behavior and identify critical factors influencing churn using interactive Power BI visualizations.
Model to Predict if a customer will purchase a Travel Package
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