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Developing Time Series Models with the Python Machine Learning Client for SAP HANA
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Training an SAP HANA PAL Univariate Time Series Model
Understanding Machine Learning for Time Series Forecasting
Providing an Overview of Time Series Models
10 mins
Exploring the Demo Scenario- Forecasting Overnight Stays
10 mins
Quiz
Setting Up the Environment and Preparing Data Using SAP HANA DataFrames
Training an SAP HANA PAL Univariate Time Series Model
Forecasting with Multiple Time Series
Knowledge quiz
It's time to put what you've learned to the test, get 3 right to pass this unit.
1.
Which of the following steps are part of training a univariate time series model using SAP HANA PAL?
There are three correct answers.
Splitting the data into training and testing datasets
Using the AutoARIMA algorithm from hana-ml
Aggregating multiple time series in a single model
Calling the fit() method to train the model
2.
The SAP HANA PAL univariate time series model in this course uses historical data from multiple variables.
Choose the correct answer.
True
False
3.
Which function is used to forecast future values in an SAP HANA PAL univariate model?
Choose the correct answer.
predict()
forecast()
transform()
evaluate()