The project is about the level of damage to the building that was hit by the 2015 Gorkha earthquake in Nepal. Their data was collected through surveys by Kathmandu Living Labs and the Central Bureau of Statistics, which works under the National Planning Commission Secretariat of Nepal. The dataset consists of information on the buildings' structure and their legal ownership, each row in the dataset represents a specific building in the region that was hit by the Gorkha earthquake. Their objective is to predict which buildings in Nepal were most susceptible to earthquake damage based on building makeup and location.
Three things I like:
I like the significance of the project. Since Nepal and its surrounding countries have earthquakes frequently, which affects countless people and families, this project helps identify beneficiaries eligible for government assistance for housing reconstruction
I also like the application of their model in home/earthquake insurance resource allocation, allowing insurance companies to predict the cost of claims and identify locations to prioritize.
I also like how the dataset is informative: it consists of a sufficient amount of features, and each of the features are described clearly with many of which are relevant to the proposed question.
Three things to improve upon:
Since this is a competition, many others are doing this project. How can you differentiate your project from the existing ones? This could be something to consider to help your project stand out among other groups.
This dataset consists of 39 columns. You may be cautious of not incorporating too many features in your prediction to avoid overfitting.
There are different kinds of values and some missing values in the dataset, what do you plan to do to deal with them? It could be helpful to explain ideas after exploring the data.
The project is about the level of damage to the building that was hit by the 2015 Gorkha earthquake in Nepal. Their data was collected through surveys by Kathmandu Living Labs and the Central Bureau of Statistics, which works under the National Planning Commission Secretariat of Nepal. The dataset consists of information on the buildings' structure and their legal ownership, each row in the dataset represents a specific building in the region that was hit by the Gorkha earthquake. Their objective is to predict which buildings in Nepal were most susceptible to earthquake damage based on building makeup and location.
Three things I like:
I like the significance of the project. Since Nepal and its surrounding countries have earthquakes frequently, which affects countless people and families, this project helps identify beneficiaries eligible for government assistance for housing reconstruction
I also like the application of their model in home/earthquake insurance resource allocation, allowing insurance companies to predict the cost of claims and identify locations to prioritize.
I also like how the dataset is informative: it consists of a sufficient amount of features, and each of the features are described clearly with many of which are relevant to the proposed question.
Three things to improve upon:
Since this is a competition, many others are doing this project. How can you differentiate your project from the existing ones? This could be something to consider to help your project stand out among other groups.
This dataset consists of 39 columns. You may be cautious of not incorporating too many features in your prediction to avoid overfitting.
There are different kinds of values and some missing values in the dataset, what do you plan to do to deal with them? It could be helpful to explain ideas after exploring the data.