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AML-Project

Final Project for Applied Machine Learning COMSW4995

Group members:

Antoni Liria Sala (al4541), Rachel Oberman (rao2140), Sahil Chandan Bhave (sb4865), Varun Agarwal (va2515), Youssef Mokssit (ym3001)

The goal of the project is to use Walmart store and economic data in order to accurately predict sales for Walmart stores in the US. The proposed machine learning solution aims to capture variations in sales data using historical sales data as well as factors such as economic conditions including Consumer Price Index (CPI), Unemployment Index as well as data for Walmart’s promotional markdown events celebrations such as Super Bowl, Labour Day, Thanksgiving, and Christmas. By considering both macro and micro-economic indicators as well as historical sales data for Walmart, we aim to model the effects of these different features and accurately predict weekly sales for Walmart stores during specific time periods.

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Columbia Data Science - Applied Machine Learning Project

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