This project tries to predict a building's damage level during an earthquake. Using data from Kathmandu Living Labs and the Central Bureau of Statistics of Nepal, the students try to fit models that would do the above job. At this stage, the group performed initial data cleaning with some insightful EDA and trained a regression model.
Things I liked:
Your histograms and other descriptive diagrams are useful for supporting your EDA and data cleaning. Overall your EDA is extremely useful in helping readers understand the data.
Your pre-processing steps such as normalization and standardization are crucial for future work. Nice job on this!
Your use of the heat map is very intuitive in describing the correlations between different variables.
Areas of Improvement:
Have you considered including data from other sources into your consideration? That would make a model that is even more generalizable.
You could add some tuning of your hyperparameters. This should dramatically improve your model's performance.
Your document spacing could be improved for your report to be more readable.
This project tries to predict a building's damage level during an earthquake. Using data from Kathmandu Living Labs and the Central Bureau of Statistics of Nepal, the students try to fit models that would do the above job. At this stage, the group performed initial data cleaning with some insightful EDA and trained a regression model.
Things I liked:
Areas of Improvement:
Overall great job!