- Deploy the Model
-
Concept | Deploy the Model 4 min
Deploy the Model
-
Tutorial | Get Started
-
Tutorial | Deploy the Model 5 min
Concept Summary: Deploy the Model
- Scoring Data
-
Concept | Scoring Data 4 min
Scoring Data
-
Tutorial | Score New Data 5 min
Hands-On: Scoring Data
- Evaluate Models
-
Concept | Model Validation and Evaluation 5 min
Model Lifecycle Management
-
Concept | Model Evaluation Stores
-
Concept | Model Comparisons
-
Quiz: Evaluate Models 3 min
- Wrap Up
-
Course Checkpoint: Scoring Basics 7 min
-
Tell Us What You Think 1 min
-
Course Complete
Scoring Basics
After finishing Machine Learning Basics, learn how to deploy prediction models to score new data.
The Scoring Basics Course follows the Machine Learning Basics course. It provides a first hands-on overview of how to apply prediction models to new data, while also managing the model lifecycle. Completion of this course will enable you to move on to more advanced courses in the ML Practitioner learning path.
Throughout the hands-on lessons, we will continue with the Haiku T-Shirts project we created in Basics 101-103, and apply the prediction model built in the Machine Learning Basics course to classify new customers as high revenue or not.
|
Learning Objectives
At the end of this course, you will be able to:
1 - Deploy a model from the Lab to the Flow
2 - Prepare an unlabelled dataset for scoring
3 - Apply a prediction model to an unlabelled dataset
4 - Understand the basics of model lifecycle management
Course Properties
Course Title | Scoring Basics |
Target Audience |
Anyone who wants to get started with visual machine learning in Dataiku DSS |
Access Level |
Free / included with registration |
Estimated Time for Completion |
58 Minutes |
Completion Criteria |
Pass the course checkpoint with 80% |
Supplemental Materials (Y/N) |
NONE |
Knowledge Prerequisite(s) |
Machine Learning Basics |
Technical Prerequisite(s) |
Dataiku DSS - Latest version (FREE EDITION is enough) |