Matching Products Across Two Online Shops

The competition among online shops in consumer electronics is tough. Customers can easily find the best price on different websites, like PriceGrabber, and industry giants, like Amazon, must respond quickly to price changes among their competitors.

This project is about matching product records across two datasets, each representing an online shop for consumer electronics. We will cover applying classic techniques and modern alternatives based on pretrained LLMs, fitting and refining a powerful black-box classification model using active learning, and interpreting the model's inner workings with SHAP.