Authors: Itamar Zaltsman, Karishma Shah, Roy Yanovski

This work was done as the final project of a Data Science course. We chose a Kaggle competition (https://www.kaggle.com/c/shopee-product-matching/) as our challenge for this project. The following article describes the dataset, our workflow, and the challenges we encountered, including also our best solution and the way we achieved it.

Introduction

E-commerce is a growing industry that has become a notable part of many people's consumption habits. The advantages of e-shopping are the quickness and easiness by which one can make a purchase, as well as the exposure to a variety of sellers and products…


ebay as a case study for product price analysis and prediction

E-commerce continues to grow and expand, with an extra boost given during covid time. Online B2C sales are predicted to generate $4.9 trillion in 2021, which is a major increase after generating $1.3 trillion in 2014. Increasing number of people today use the internet to purchase different products, from groceries to laptops, and even cars. The main challenge online consumers face is the high abundance and variety of products and sellers. Everyone wants to get the best deal. A good quality product in the lowest price available. That being said, searching through hundreds of pages and scanning thousands of products…

Roy Yanovski

PhD candidate, Marine biologist, Data scientist, and nature enthusiast. Interested in using data science to make the world a better place.

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