Integrate with Beam

This notebook is designed to provide you with the context you need to navigate Beam API effectively.

Beam is PredictHQ's automated correlation engine to accurately reveal the events that drive demand for your business. It not only highlights the correlation between events and your demand data but also offers a decomposition of your demand data, aiding in enhancing the precision of your demand forecasts. For a deeper dive into Beam, explore the Beam Overview.

Our objective through this notebook is to navigate you through the following use cases facilitated by the Beam API:

  1. Upload demand data to Beam: Upload your data to Beam for analysis.

  2. Generate Beam analysis results: Generate Beam analysis results between events and your demand data using Beam.

  3. Plot and interpret Beam output: Visualize and interpret the output from Beam for better insights.

  4. Identify relevant features using Feature Importance: Explore Feature Importance to identify and extract relevant features for your forecasting model.

Utilizing Beam's decomposition and the Feature Importance feature can substantially augment the accuracy of your forecasts. If you have not been decomposing your data for forecasting purposes, Beam’s functionalities provide a robust framework to dissect your data into baseline demand and remainder components, coupled with identifying critical features essential for an accurate forecasting model.

For additional insights into the Beam API, please refer to our technical documentation.

You can find the notebook on Github.

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