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š Iām currently working on A model for Credit Risk Assessment using XGBoost
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šØāš» All of my projects are available at https://github.com/Owadd?tab=repositories
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š« How to reach me [email protected]
Name: Owadokun Oluwatobi Ezekiel
Type: User
Bio: Hi there! Iām Oluwatobi, a Pythonic Finance developer with a passion for Finance, Banking and Python programming.
Location: Lagos, Nigeria.
š Iām currently working on A model for Credit Risk Assessment using XGBoost
šØāš» All of my projects are available at https://github.com/Owadd?tab=repositories
š« How to reach me [email protected]
This project aims to predict credit risk for individuals applying for loans, classifying whether they will default based on features such as age, income, employment length, loan amount, interest rate, percentage of income, credit length, home ownership, and loan intent.
Developed a model to predict customer churn for subscription-based businesses.
Config files for my GitHub profile.
A simple and interactive web application built with Streamlit to help users estimate their retirement savings. Users can input their current age, desired retirement age, current savings, annual contributions, and expected return rate.
This Python project analyzes public sentiment on social media (like Twitter) towards cryptocurrencies and it leverages Support Vector Machines (SVM) for sentiment classification.
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China tencent open source team.