AUTO SARIMA Example 

This workflow demonstrates how the SARIMA components can be used to generate forecasts. In this case for hourly temperature data.

LSTM_​TS_​Predictions 

LSTM Network This workflow predicts the irregular component of time series (energy consumption) by an LSTM network with lagged values as input. The […]

02_​LSTM_​Network 

This workflow predicts time series (energy consumption) by an LSTM network with lagged values as input. The trained model is then used for out-of-sample […]

3_​Zeitjustierung 

02_​Inspect_​and_​Remove_​Seasonality 

This workflow shows the seasonality of time series (energy consumption) in an autocorrelation plot. The seasonality is removed by differencing the time […]

KT_​PP-G1 

This workflow predicts time series (energy consumption) by an LSTM network with lagged values as input. The trained model is then used for out-of-sample […]

08_​LSTM_​Network 

Time Series Analysis 07. LSTM Network Summary: In this exercise we'll define an LSTM Network Architechure to train and deploy on the Time Series. […]

Data App - Guess the Flag Game 

The behavior of each page can be customized as needed using widgets, refresh button, loops, conditional paths etc..

ARIMA Example 

This workflow predicts the irregular component of time series (energy consumption) by autoregressive integrated moving average (ARIMA) models that aim at […]

04_​Machine_​Learning 

This workflow predicts the residual of time series (energy consumption) by machine learning models that use lagged values as predictors. The residual of […]