Aplicação de Aprendizado de Máquina para Predição do Preço da Cesta Básica

Resumo

ABSTRACT
Four foods from the Brazilian Basic Basket were chosen for
KDD application to predict future prices with their trends and
causes, if they are related to the data sources used in the
research. To predict prices, the Holt-Winters method was
used, and to define the trend, K-Means was used. The tools
used in this development were Jupyter Notebook, Anaconda,
Excel, PostgreSQL, Docker, 2UDA Orange3 and the Python
language, with its main libraries related to data science, such
as Pandas, NumPy, Matplotlib and Seaborne.