von Sachs, RainerGueulette, ArnaudArnaudGueulette2025-05-142025-05-142025-05-142023https://hdl.handle.net/2078.2/34676This thesis mainly discusses forecasting competitions and how they contribute to the field of forecasting. It also discusses the winner of the M4 competition, a hybrid model that blends statistical and deep learning concepts. The model, called Exponential Smoothing Recurrent Neural Network (ES-RNN), was proposed by Slawek Smyl, a data scientist at Uber. This hybrid model outperformed all other models in the M4 competition, pointing the way for further development and research into more complex methods.Time SeriesForecastingDeep LearningMachine LearningHybrid ModelsStatisticsData Sciencetext::thesis::master thesisthesis:43191