Customer Shopping Preference Prediction using Machine Learning

Built a complete machine learning pipeline to analyze and predict customer shopping preferences (Online vs Store Shopping) using Python and Scikit-learn.

The project included:

Data Cleaning & Preprocessing

Exploratory Data Analysis (EDA)

Data Visualization

Feature Engineering

Handling Imbalanced Data using SMOTE

Training multiple ML models

Evaluating models using Accuracy, Precision, Recall, and F1-Score

The models used included:

Logistic Regression

Random Forest

Stacking Classifier

sThe project achieved high classification performance, with Logistic Regression showing strong overall result