BHT_Store_Sales_Time_Series_Forecasting

This is a project done in the learning optimazation class. The data is from a previous kaggel competition: https://www.kaggle.com/competitions/store-sales-time-series-forecasting/overview/frequently-asked-questions

The final report is the Learning_Optimazation_Report.pdf

• The EDA + Exponential Smoothing + Double Exponential Smoothing and SARIMA model can be found here
• The Prophet model was build here
• The Tree base models were build in file "Decision Tree and Random Forest.ipynb".
• The creation of the distribution for Top-Down approach can be found here

Project focal points:

• Demand Forecasting / Time Series Forecasting
• Feature Engineering
• Hyperparameter Tuning as Optimization
• Model Selection as Optimization

The project should focus on at least one of the following three tasks:

• comparing different time series forecasting models
• optimizing the hyperparameters of a ML or Deep Neural Network
• automizing the model selection