This repository contains code and solutions for the Data Mining project, which applies various techniques and methods to different datasets. The project covers data preprocessing, dimensionality reduction, regression, classification, and association rule mining.
This section includes a notebook for data cleaning, normalization, and dimensionality reduction using Principal Component Analysis (PCA).
This section explores various regression and classification techniques applied to the e-commerce dataset, including linear regression, logistic regression, and other classification algorithms.
This section covers the application of association rule mining techniques to identify relationships and patterns within the e-commerce data.
The final project integrates all the techniques covered in the previous sections to analyze the e-commerce dataset comprehensively.