Deep Learning and Traditional Methods: A Critical Comparison for Sales Forecasting in the Pharmaceutical Sector

The objective of this thesis is to provide an overview of the pharmaceutical company SIFI and to forecast its sales. To achieve this, we will consider various analytical models, ranging from simple regression analysis to more complex deep learning architectures such as LSTM. We will compare the results across models and aim to identify the best-performing one.