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Saniya Abushakimova's Projects

a-study-of-sigmoid-based-multi-class-logistic-regression icon a-study-of-sigmoid-based-multi-class-logistic-regression

Investigated how multi-class logistic regression would perform if the activation function was changed from softmax to sigmoid. It included mathematical analysis and empirical evaluation, such as rewriting the model from scratch. Tech: Python (Scikit-Learn, Pandas)

customer-clustering icon customer-clustering

Conducted customer clustering, made detailed description for each customer group, and made churn analysis of the customers.

predicting-life-satisfaction-rate-with-multiple-linear-regression icon predicting-life-satisfaction-rate-with-multiple-linear-regression

Analyzed what factors influence the level of satisfaction of people living in developing countries. The analysis contained predictor subset selection with VIF, Mallow’s Cp and BIC scores, model validation, and remedial measures. The model performance was evaluated based on hypothesis testing. Tech: R (RStudio)

red-wine-quality-classification-using-supervised-learning icon red-wine-quality-classification-using-supervised-learning

Conducted data analysis using statistical tools and complex visualizations; trained logistic regression, k-nn, kernelized svm, and random forest models; performed hyperparameter tuning and error analysis. Tech: Python (Seaborn, Matplotlib, Pandas, Scikit-Learn)

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