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credit-risk.github.io

This project explores credit card approval risk using machine learning. It covers data preprocessing, visualization, and comparisons of models like Logistic Regression and Random Forest. Key results show Random Forest and Logistic Regression achieving around 86% accuracy. 🚀📊

gender-effect-of-financial-analyst-forecast-during-covid-19

This project analyzes the impact of Covid-19 on the work quality of female financial analysts versus their male counterparts, examining gender-based differences in behavior, performance, and influence on investor decisions through earnings forecasts.

nlp-movie-sentiment-classification

This application utilizes Artificial Neural Networks (ANN), Recurrent Neural Networks (RNN), and Transformer models to detect and analyze sentiment in user-provided reviews.

raddit-data

tank-war

🎮 The Tank War game application written in pygame.

xu000112-bit