This project is about the damage done by earthquakes to the buildings in Nepal. It aims to predict what buildings may be affected by the earthquakes. The data is from the 2015 earthquake in Nepal.
Good Points:
The dataset includes large amount of other categorial and informative pieces that help to understand the broader context of the buildings - e.g. age, who may use these more, socioeconomic class.
The project proposal offers real world applications as to why this problem or this data offers value. It can help inform resource allocation to help safeguard buildings to prevent loss of life or destruction to historical buildings in the future.
The model may be applicable to other areas, not just Nepal, that have earthquakes nearby. It could be used in a greater context for those that suffer from earthquakes globally.
Improvement Points:
Do you plan to work with values that may be missing or invalid? Some buildings may be destroyed. Do we have the data on those that were truly hardest hit?
Is it possible to take into account the different countries? How do you plan on integrating that?
Are you planning on generalizing the model? It seems like it could be and was sightly suggested, but is not fully clear.
This project is about the damage done by earthquakes to the buildings in Nepal. It aims to predict what buildings may be affected by the earthquakes. The data is from the 2015 earthquake in Nepal. Good Points:
Improvement Points: