Timeseria-notebooks

Example notebooks using Timeseria: an object-oriented time series processing library.

⚠️ The plots in these notebook are configured to be rendered as images, because otherwise they won't display correctly on GitHub or when the notebooks are loaded (usually because not trusted).

Available notebooks:

• A Million Points
• Anomaly detection - Temperature and humidity - LSTM
• Forecasting - Advanced Evaluation.ipynb
• Forecasting - Temperature - Periodic Averages.ipynb
• Forecasting - Temperature and humidity - LSTM.ipynb
• Forecasting - Temperature - LSTM - Probabilistic calibration.ipynb
• Forecasting - Temperature - Probabilistic LSTM.ipynb
• Forecasting - Temperature - Probabilistic Periodic Averages.ipynb
• Operations.ipynb
• Plotting.ipynb
• Quickstart.ipynb
• Welcome.ipynb

You can also run them interactively using the Timeseria Docker container:

docker run -it -p8888:8888 -v$PWD/notebooks:/notebooks sarusso/timeseria:v2.3.0

Or, you can install Timeseria (pip install timeseria) and run them within your own environment. In this case please ensure Timeseria >= v2.3.