Objective

As the pandemic continues, demand of delivery services on food and goods are staying sky high, how customers optimize their bucket items to maximize multiple discounts provided to reach the delivery minimum amount is critical to keep down per purchase cost.

Methodology

Scraping item information like categories, SKU, price, availability, delivery status from HKTV mall, automating pipeline to periodically fetch them into machine learning models, evaluating recommender to best optimize the cost and maximize discount used.

Insight

Pretty decent to fetch data into web-based API then return a best combination of food items based on inputted recipes (like recipe recommendations based on refrigerator items).