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Modeling and forecasting time series using deep learning

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Activating the virtual environment

For the creation of virtual environments (VE) anaconda is used. You can download anaconda here: https://www.anaconda.com/distribution/

After installing anaconda into your system follow the steps bellow to work in a virtual environment.

Creation of the VE:

conda create python=3.7 --name deep-ts

Activating the VE:

conda activate deep-ts

Installing all the packages from the requirements.txt file to the virtual environment:

pip install -r requirements.txt

If you are using Microsoft Visual Studio code there may be some additional pop ups indiciating that some packages should be installed (linter or ikernel).

Time series data

The data is taken from: https://www.kaggle.com/robikscube/hourly-energy-consumption. The data is an hourly time series regarding the power consumption (in MW) in the Dayton region. The data spans from 2004-10-01 to 2018-08-03 (n=121271)

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