Time Series Project Setup in DataRobot
Learn how to set up a time series project in DataRobot, including selecting features, choosing a prediction target, and adjusting experiment settings.
00:00:07 Learn how to start a DataRobot Time Series project, define settings, and understand defaults. GUI and Python API paths produce the same outcome. Use publicly available data set.
📊 Learn how to start a DataRobot Time Series project and define initial settings.
🔧 Understand the importance of controlling experiment settings and default configurations.
💻 Demonstrate starting a Time Series project through the graphical user interface and DataRobot Python API.
00:01:15 Learn how to set up a time series project in DataRobot, including selecting features, choosing a prediction target, and adjusting experiment settings.
📝 The video is about setting up a time series project in DataRobot.
🔍 There are eight raw features and nine informative features in the project.
⏱️ The video explains how to choose the date feature and use automated time series forecasting.
00:02:25 Learn how to configure project settings and start the modeling process in DataRobot for time series analysis.
🔍 The video discusses the default settings for back testing and time series modeling in DataRobot.
⚙️ Advanced options for date time partitioning and time series settings are available in DataRobot.
📊 The tutorial demonstrates how to change the modeling mode, start the process, and increase the number of workers in DataRobot.
00:03:35 This video covers the project settings for time series models in DataRobot, including the dataset ID, feature to be predicted, and date time column.
📦 Package and connect to DataRobot
📊 Specify project settings and feature to predict
⏱️ Create a project in AutoPilot mode and monitor progress
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