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Implemented Feature Selection, Regularization, and Dimension Reduction, followed by Model Selection to predict sales and identify profitable markets for a retail firm.

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Market-Analysis-based-on-Machine-Learning-techniques

In collaboration with my stimated collegue Ortensia Forni

Implementation of Feature Selection (Best Subset Selection), Regularization (Lasso and Ridge), Dimension Reduction (PCA and PLS) followed by the execution of Model Selection (linear and polynomial regression, GAM, decision trees, random forest, gradient boosting, SVM, NN) to predict sales of a fictitious multinational retail company and to select the most profitable market to open

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Implemented Feature Selection, Regularization, and Dimension Reduction, followed by Model Selection to predict sales and identify profitable markets for a retail firm.

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