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Richter's Predictor - Nepal Earthquake 2015

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Source (Credits) to the problem statement: DrivenData

Following the 7.8 Mw Gorkha Earthquake on April 25, 2015, Nepal carried out a massive household survey using mobile technology to assess building damage in the earthquake-affected districts. Although the primary goal of this survey was to identify beneficiaries eligible for government assistance for housing reconstruction, it also collected other useful socio-economic information. In addition to housing reconstruction, this data serves a wide range of uses and users e.g. researchers, newly formed local governments, and citizens at large. The purpose of this portal is to open this data to the public.

The objective is to predict the ordinal variable damage_grade, which represents a level of damage to the building that was hit by the earthquake. There are 3 grades of the damage:

1 represents low damage
2 represents a medium amount of damage
3 represents almost complete destruction

Other details can be referred by clicking on the source link provided above

!pip install jovian --upgrade --quiet
!pip install numpy pandas matplotlib seaborn --quiet
!pip install jovian opendatasets xgboost graphviz lightgbm scikit-learn xgboost lightgbm --upgrade --quiet