Jupyter notebook implementing time series forecasting of energy consumption data with different techniques:
At first make sure to have Python 3.6 or higher and Jupyter notebook installed. To run the notebook execute the following commands:
python -m pip install pipenv
python -m pipenv shell
pipenv install
python -m ipykernel install --user --name=<folder_name>
jupyter notebook
Now you should be able to execute the code in the notebook with all related dependencies installed.
You can also play with the ML forecasting models using the CLI script
contained in the src
folder. After having install the dependencies you can execute
the script with the following command inside the src
folder:
# available commands
python main.py --help
# 48 steps ahead forecast using recursive technique
python main.py --steps 48 --fcast recursive