Analysis of the Online Home Consumption Database Based on Data Mining

Abstract

In current times where there are smart devices for households, and that apart from having different functions that are helpful in daily household chores, such as being able to maintain a full pantry, and to generate errand lists, in the market these devices have a high cost for this reason is that it is proposed to create a low cost smart device, in this document an analysis is made using data mining, with tensor flow, of the purchases generated by the users, derived from the current situation by the pandemic of the COVID-19, generated an increase in online shopping, this analysis is intended to be a support for online errand shopping to visualize classification and prediction in the comparisons of users.