PCA Insights is a data analysis project aimed at applying Principal Component Analysis (PCA) to high-dimensional datasets for dimensionality reduction, visualization, and exploration.
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Nov 26, 2024 - Jupyter Notebook
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dimensionalityreduction
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High-dimensional loan transaction data. By reducing the dimensionality of the dataset, patterns were identified to help a financial institution mitigate risks such as loan defaults or early repayments. Key steps include data preprocessing, PCA implementation, and interpretation of principal components to uncover significant insights.
exploratory-data-analysis loananalysis riskmanagement pythonprogramming dimensionalityreduction principalcomponentanalysis financialanalytics
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Jan 22, 2025 - Jupyter Notebook
here is where I practice data analysis and machine learning
python clustering storytelling regression classification machinelearning datavisualization datapreprocessing datascience-machinelearning dimensionalityreduction
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May 20, 2021 - Jupyter Notebook
Data science project applying feature selection/dimensionality reduction techniques to identify the explanatory variables to be included within a linear regression model that predicts the number of times an online news article will be shared using Python 3 in a Juypter Notebook.
sklearn python3 k-fold-cross-validation juypter-notebook featureselection dimensionalityreduction linearreggresion
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Dec 11, 2023 - Jupyter Notebook
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