Course

Model Training Deep Dive: Discover

  • 9026 enrolled students
  • November 24, 2023
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Model Training Deep Dive: Discover

  • 000:45:00
  • Downloadable resources available
  • Diploma of Completion included
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Course details

Difficulty Level

Beginner

Language

English

Completion time

000:45:00

Product covered

UiPath Communications Mining

Are you interested in learning about the 'Discover' phase of model training? Our comprehensive course is designed to help you understand the importance of this critical step in the model training process. 

 

About the Model Training Deep Dive: Discover course 

This course is meant to provide technical audiences and business users with an understanding of the 'Discover' phase of the model training process.  

It provides an insight into the importance of clusters, as well as explains in detail how to label clusters and how to label verbatims using search. 

The Model Training Deep Dive: Discover course takes 45 minutes to complete. At the end, you’ll receive a diploma of completion. 

 

Course prerequisites 

To enjoy this learning experience, we recommend you going through the following courses: 

  • UiPath Communications Mining Overview 
  • Fundamentals of Model Training 
  • Taxonomy Design 
  • Model Training Deep Dive: Setup 

 

Course audience 

The Model Training Deep Dive: Discover course is aimed at technical audiences and business users, as well as anybody else curious to see the power of Natural Language Processing in business. 

 

The Model Training Deep Dive: Discover course agenda 

The full agenda covers:  

  • What is the 'Discover' Phase? 
  • Understanding Label and Entity Predictions 
  • How to Train Using ‘Clusters' 
  • How to Train Using ‘Search’ 
  • How to Use ‘Train’ During the ‘Discover’ Phase 
  • Practice: Train Your Model in the 'Discover' Phase 

 

Model Training Deep Dive: Discover course learning objectives 

At the end of the Model Training Deep Dive: Discover course, you should be able to: 

  • Define what the 'Discover' phase of training is, how it works, and why it is important. 
  • Explain how label and entity predictions work, and how to use them. 
  • List out the important considerations while labeling in 'Discover'. 
  • Navigate through 'Clusters'. 
  • Train different 'Clusters'. 
  • Train using 'Search'. 
  • Explain why 'Search' should be used sparingly. 
  • Use 'train' during the 'Discover' phase.