The goal is to provide insightful and visually appealing representations of key nutritional metrics, enabling better understanding and healthier choices for consumers.

This collection showcases a diverse range of machine learning models and data analysis projects, each designed to extract meaningful insights from unique datasets. The portfolio demonstrates a comprehensive approach to data-driven decision-making, with a strong emphasis on thorough data exploration. Each project is housed its own dedicated repo.

Offer optimization using machine learning techniques with Starbucks dataset.

Official Starbucks Nutritional dataset

Built a predictive pipeline to optimize customer targeting for Starbucks promotions.

An analysis and visualization of Starbucks Customer Data

Review basic web development concepts through a coffeeshop project