This research goal is to build binary classifier model which are able to separate fraud transactions from non-fraud transactions.
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Updated
Nov 14, 2023 - HTML
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.
Project for insurance churn prediction with xgboost classification algorithm
Modelling and prediction of default + deployment via AWS Sagemaker
👨🏼⚕️🧠 Web-App predicting brain drain in AI research at public institutions
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.
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.
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.
Model to Predict if a customer will purchase a Travel Package
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.
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