NLP - The Visual Way

NLP - The Visual Way

Learn how to prepare and model natural language data with visual tools in Dataiku DSS.

About this course

 

“NLP - The Visual Way” is a course dedicated to natural language processing using visual tools in Dataiku DSS. It assumes a basic familiarity with visual machine learning in Dataiku DSS.

 

In the hands-on lessons, we will work with a dataset of movie reviews. Our task will be to build models to classify reviews as positive or negative.


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 look at a simple example of classifying SMS messages as spam or not-spam.

 

 

Learning Objectives

At the end of this course, you will be able to:

1 - Understand the goals and challenges of Natural Language Processing (NLP)

2 - Prepare a dataset for NLP tasks with transformations like normalization, stopwords removal, and stemming

3 - Apply different strategies for handling text features in machine learning tasks and understand the tradeoffs between them

 

Course Properties

Course Title NLP - The Visual Way

Target Audience

Anyone with a basic understanding of visual machine learning in Dataiku DSS and wants to work with natural language data

Access Level

Free / included with registration

Estimated Time for Completion

70 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 and Scoring Basics required

Technical Prerequisite(s)

Dataiku DSS - Latest version (FREE EDITION is enough)

 

Start by watching the course overview video and by looking at some key concepts: The Goal of NLP, Preparing Text Data, and Handling Text Features for ML.

Curriculum70 min

  • Course Introduction
  • Preview
    Course Introduction: NLP - The Visual Way 1 min
  • Introduction to NLP
  • Concept: The Goal of NLP 3 min

    Concept: The Goal of NLP

  • Concept Summary: The Goal of NLP 3 min

    Concept Summary: The Goal of NLP

  • Hands-On: The Goal of NLP 5 min

    Hands-On: The Goal of NLP

  • Quiz: Introduction to NLP 3 min

    Quiz: Introduction to NLP

  • Preparing Text Data
  • Concept: Challenges of NLP 4 min

    Concept: Challenges of NLP

  • Concept: Cleaning Text Data 4 min

    Concept: Cleaning Text Data

  • Concept Summary: Preparing Text Data 4 min

    Concept Summary: Preparing Text Data

  • Hands-On: Preparing Text Data 5 min

    Hands-On: Preparing Text Data

  • Quiz: Preparing Text Data 3 min

    Quiz: Preparing Text Data

  • Handling Text Features for ML
  • Concept: Handling Text Features for ML 7 min

    Concept: Handling Text Features for ML

  • Concept Summary: Handling Text Features for ML 7 min

    Concept Summary: Handling Text Features for ML

  • Hands-On: Handling Text Features for ML 8 min

    Hands-On: Handling Text Features for ML

  • Quiz: Handling Text Features for ML 3 min

    Quiz: Handling Text Features for ML

  • Wrap Up
  • Course Checkpoint 7 min

    Course Checkpoint

  • Tell Us What You Think 1 min
  • Course Complete 1 min

About this course

 

“NLP - The Visual Way” is a course dedicated to natural language processing using visual tools in Dataiku DSS. It assumes a basic familiarity with visual machine learning in Dataiku DSS.

 

In the hands-on lessons, we will work with a dataset of movie reviews. Our task will be to build models to classify reviews as positive or negative.


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 look at a simple example of classifying SMS messages as spam or not-spam.

 

 

Learning Objectives

At the end of this course, you will be able to:

1 - Understand the goals and challenges of Natural Language Processing (NLP)

2 - Prepare a dataset for NLP tasks with transformations like normalization, stopwords removal, and stemming

3 - Apply different strategies for handling text features in machine learning tasks and understand the tradeoffs between them

 

Course Properties

Course Title NLP - The Visual Way

Target Audience

Anyone with a basic understanding of visual machine learning in Dataiku DSS and wants to work with natural language data

Access Level

Free / included with registration

Estimated Time for Completion

70 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 and Scoring Basics required

Technical Prerequisite(s)

Dataiku DSS - Latest version (FREE EDITION is enough)

 

Start by watching the course overview video and by looking at some key concepts: The Goal of NLP, Preparing Text Data, and Handling Text Features for ML.

Curriculum70 min

  • Course Introduction
  • Preview
    Course Introduction: NLP - The Visual Way 1 min
  • Introduction to NLP
  • Concept: The Goal of NLP 3 min

    Concept: The Goal of NLP

  • Concept Summary: The Goal of NLP 3 min

    Concept Summary: The Goal of NLP

  • Hands-On: The Goal of NLP 5 min

    Hands-On: The Goal of NLP

  • Quiz: Introduction to NLP 3 min

    Quiz: Introduction to NLP

  • Preparing Text Data
  • Concept: Challenges of NLP 4 min

    Concept: Challenges of NLP

  • Concept: Cleaning Text Data 4 min

    Concept: Cleaning Text Data

  • Concept Summary: Preparing Text Data 4 min

    Concept Summary: Preparing Text Data

  • Hands-On: Preparing Text Data 5 min

    Hands-On: Preparing Text Data

  • Quiz: Preparing Text Data 3 min

    Quiz: Preparing Text Data

  • Handling Text Features for ML
  • Concept: Handling Text Features for ML 7 min

    Concept: Handling Text Features for ML

  • Concept Summary: Handling Text Features for ML 7 min

    Concept Summary: Handling Text Features for ML

  • Hands-On: Handling Text Features for ML 8 min

    Hands-On: Handling Text Features for ML

  • Quiz: Handling Text Features for ML 3 min

    Quiz: Handling Text Features for ML

  • Wrap Up
  • Course Checkpoint 7 min

    Course Checkpoint

  • Tell Us What You Think 1 min
  • Course Complete 1 min