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Course Introduction: Partitioned Models 0 min
- Create a Partitioned Model
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Concept: Partitioning 3 min
Concept: Partitioning
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Concept: Partitioned Models 5 min
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Concept Summary: Partitioned Models 2 min
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Hands-On: Partitioned Models 5 min
- Wrap Up
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Course Checkpoint: Partitioned Models 6 min
Course Checkpoint
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Tell Us What You Think 1 min
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Course Complete 1 min
Course Complete
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Partitioned Models
Learn how to train a machine learning model on partitions of your dataset.
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Partitioned Models demonstrates how to build a partitioned model trained on subgroups, or partitions, of the dataset, and compare the results with a non-partitioned model trained on the whole dataset.
In the hands-on lesson, we will work with flight data. We will predict the arrival delay time for a given flight based on the flight's characteristics, such as departure delay time. Before the hands-on section, you will have a chance to grasp the concept of partitioned models by watching short videos.
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Learning Objectives
At the end of this course, you will be able to:
1 - Describe partitioned models to a colleague
2 - Create a partitioned model from a partitioned dataset in Dataiku DSS
3 - Compare results from a non-partitioned model with the partitioned model
Course Properties
| Course Title | Partitioned Models |
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Target Audience |
Anyone who wants to learn how to create partitioned models in Dataiku DSS |
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Access Level |
Free / included with registration |
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Estimated Time for Completion |
24 Minutes |
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Completion Criteria |
Pass the course checkpoint with 80% |
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Supplemental Materials (Y/N) |
NONE |
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Knowledge Prerequisite(s) |
NONE |
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Technical Prerequisite(s) |
Dataiku DSS - Latest version (FREE EDITION is enough) |
Start by watching the Partitioned Models course overview video.