In this notebook, I developed a model aimed at predicting eathquake in Kavrepalanchok.. The purpose is to obtain the best model and the best depth for the prediction and to emphasize on the various steps needed to build such a model. I also explained the possible methods to deploy the model, these include wrapping the model in a function so that a programmer can provide inputs and then receive a prediction as output or creating an interactive dashboard, where a user can supply values and receive a prediction.
The was queried from a database comprising of four tables (id_map, building_structure, building damage and household_demographics) and four districts labelled 1 to 4. Myagdi is 1, Ramechhap is 2, and Gorkha is 4 of Nepal Districts.. Then, What's the district ID for Kavrepalanchok? Did you say 3?! Yes, you are right. Kavrepalanchok is district ID 3 according to our database.
Since you may not have access to this database, I have saved the results of my query as kavrepalanchok_raw.csv which can the be wrangled (cleaned). The cleaned data, kavrepalanchok_clean.csv, gotten from my wragle function has also been provided for you to make use of - this as been made specifically for this project. Finally, kavrepalanchok_test.csv is also available to check for model performance.
- Linear Regression
- Decision Tree Classifier
