Scoring Basics

Scoring Basics

After finishing Machine Learning Basics, learn how to deploy prediction models to score new data.

About this course

 

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.


Before each hands-on section, you will have a chance to grasp each new concept by watching short videos. In the concept videos, we’ll continue exploring a project to predict whether patients will be readmitted to a hospital.

 

 

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 all section waypoints with 65% and 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)

 

Start by watching the Scoring Basics course overview video and by looking at some key concepts: Deploy the Model, Scoring Data, and Model Lifecycle Management.

Curriculum63 min

  • Course Introduction
  • Preview
    Course Introduction: Scoring Basics 1 min
  • Deploy the Model
  • Concept: Deploy the Model 3 min

    Deploy the Model

  • Concept Summary: Deploy the Model 4 min

    Concept Summary: Deploy the Model

  • Hands-On: Deploy the Model 5 min

    Concept Summary: Deploy the Model

  • Quiz: Deploy the Model 3 min
  • Scoring Data
  • Concept: Scoring Data 4 min

    Scoring Data

  • Concept Summary: Scoring Data 5 min

    Concept Summary: Scoring Data

  • Hands-On: Scoring Data 5 min

    Hands-On: Scoring Data

  • Quiz: Scoring Data 3 min
  • Model Lifecycle Management
  • Concept: Model Lifecycle Management 5 min

    Model Lifecycle Management

  • Concept Summary: Model Lifecycle Management 6 min

    Concept Summary: Model Lifecycle Management

  • Quiz: Model Lifecycle Management 3 min
  • Wrap Up
  • Course Checkpoint 7 min
  • Tell Us What You Think 1 min
  • Course Complete 7 min

About this course

 

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.


Before each hands-on section, you will have a chance to grasp each new concept by watching short videos. In the concept videos, we’ll continue exploring a project to predict whether patients will be readmitted to a hospital.

 

 

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 all section waypoints with 65% and 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)

 

Start by watching the Scoring Basics course overview video and by looking at some key concepts: Deploy the Model, Scoring Data, and Model Lifecycle Management.

Curriculum63 min

  • Course Introduction
  • Preview
    Course Introduction: Scoring Basics 1 min
  • Deploy the Model
  • Concept: Deploy the Model 3 min

    Deploy the Model

  • Concept Summary: Deploy the Model 4 min

    Concept Summary: Deploy the Model

  • Hands-On: Deploy the Model 5 min

    Concept Summary: Deploy the Model

  • Quiz: Deploy the Model 3 min
  • Scoring Data
  • Concept: Scoring Data 4 min

    Scoring Data

  • Concept Summary: Scoring Data 5 min

    Concept Summary: Scoring Data

  • Hands-On: Scoring Data 5 min

    Hands-On: Scoring Data

  • Quiz: Scoring Data 3 min
  • Model Lifecycle Management
  • Concept: Model Lifecycle Management 5 min

    Model Lifecycle Management

  • Concept Summary: Model Lifecycle Management 6 min

    Concept Summary: Model Lifecycle Management

  • Quiz: Model Lifecycle Management 3 min
  • Wrap Up
  • Course Checkpoint 7 min
  • Tell Us What You Think 1 min
  • Course Complete 7 min