Understanding Machine Learning for Time Series Forecasting

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

Understanding Machine Learning for Time Series Forecasting

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.

Choose the correct answer.

To improve data compression for storage

To apply a separate model to each group or category

To reduce model training time by removing time information

To merge all variables into a single univariate forecast

Choose the correct answer.

True

False

There are two correct answers.

Aggregating grouped data into a single time series

Structuring the data so each group can be forecasted independently

Identifying the grouping dimension such as destination or product

Extracting distinct values for each group

Choose the correct answer.

A loop that filters data for each group and applies forecasting individually

A single fit() call with all grouped data passed in

A switch-case block to run one model per data format

A decision tree that assigns forecasts based on data categories

Learning