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Learn how to preprocess data, engineer features, use gradient boosting, cross validation, hyperparameter tuning, and make predictions in this course project.


Use the "Run" button to execute the code.

!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
|████████████████████████████████| 166.7 MB 18 kB/s |████████████████████████████████| 2.0 MB 34.1 MB/s |████████████████████████████████| 22.3 MB 1.3 MB/s
import jovian