In this session we will learn about basics of time series analysis, forecasting, and classification. We will also perform hands-on analysis using Python and Google Colab.
We will use Google Colab to run the demo during the practical session. You can also run the demo locally if you have Python and jupyter-notebook installed.
If you want to use Google Colab to run the demo:
- You will need a Google account.
- Download the epilepsy.csv from this repo and upload it to your main Google Drive folder.
- To open and run the notebooks or to only visualize the notebook click on the links below:
| Title | Run on Google Colab | View using Nbviewer |
|---|---|---|
| Demo 1: Forecasting |  |
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| Demo 2: Classification | |
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- statsmodels time series analysis: a time series analysis Python toolbox.
- Scikit-learn: a comprehensive machine learning Python library.
- hctsa: a Matlab software package for running highly comparative time series analysis and feature-based analysis of time series.