Predicts Daily Power Usage (in kWh), based on Weather conditions
Accuracy achieved: 70.14426%
Files present:
engine.py - Source Code, Python3 File
power_usage_prediction_1.ipynb - Source Code with IPython magic commands, Jupyter Notebook
train_inputs.parquet, train_targets.parquet - Input columns and Target column DataFrames used for Training the models, Parquet Files
test_inputs.parquet, test_targets.parquet - Input columns and Target column DatFrames for Validation, Parquet Files
Model1.joblib - sklearn.LinearRegression() model, Joblib File
Model2.joblib - sklearn.SGDRegressor() model, Joblib File
Dependencies to be installed for using the model:
pandas
joblib