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Product Demand Prediction Using Machine Learning

Student: Aleksandr Kartavchenko

Supervisor: Denis Moskvin

Faculty: St. Petersburg School of Physics, Mathematics, and Computer Science

Educational Programme: Big Data Analysis for Business, Economy, and Society (Master)

Year of Graduation: 2021

The work is devoted to forecasting the demand for various goods. The paper considers both classical methods for time series forecasting and regression methods of machine learning. In addition to the traditional problem of obtaining the value of a specific prediction, the problem of constructing a confidence interval for the predicted value is solved.

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