Customer Purchase Behavior Analysis
A customer analytics project examining retail purchase behavior and spending patterns to inform data-driven decisions.
A customer analytics project examining retail purchase behavior and spending patterns to inform data-driven decisions.
Implemented and analyzed a CNN-based image classifier in a Jupyter Notebook, focusing on model architecture, training workflow, and evaluation using deep learning techniques in Python.
An end-to-end A/B test analyzing whether a new landing page improves user conversion using statistical hypothesis testing and effect size analysis.
Implemented a K-Nearest Neighbors classifier for handwritten digit recognition achieving 97%+ accuracy on the MNIST dataset. Applied systematic hyperparameter optimization using grid search and cross-validation techniques.
A hybrid movie recommendation system using content-based and collaborative filtering techniques.
Built a Python web scraping pipeline using BeautifulSoup and Selenium to extract structured data from 100+ dynamic product pages with high reliability.