This commit adds a Jupyter notebook that implements an SEIR (Susceptible-Exposed-Infectious-Removed) model for simulating the spread of COVID-19 using real-world data. The notebook focuses on parameter optimization to fine-tune the model's parameters based on a specific COVID-19 dataset. The key features and components of this commit are as follows:

- The SEIR model is implemented using Pytorch.
- Real COVID-19 dataset is used to initialize and validate the model.
- The notebook utilizes optimization techniques to find the best-fitting parameters for the SEIR model.
- Results, visualizations, and insights are included to facilitate an understanding of the model's performance and the significance of parameter tuning.