In this session, you’ll learn about the main concepts behind Time Series: preprocessing, alignment, missing value imputation, forecasting, and evaluation. Together we will build a demand prediction application: first with (S)ARIMA models and then with machine learning models. The codeless examples are built in the KNIME Analytics Platform using the Time Series components provided for preprocessing, transforming, aggregating, forecasting, and inspecting time series data. You will also be provided example workflows to use later in your own projects.
Corey Weisinger is the creator and instructor of the KNIME Time Series Analysis course, author of the e-book, Alteryx to KNIME, and creator of the KNIME Time Series Analysis components.
Maarit Widmann is a teacher of the Introduction to Time Series Analysis course, co-author of the e-book, From Modelling to Model Evaluation, and author of a series of codeless blueprints for financial data analysis.