Course 3B: Natural Language Processing in Driverless AI

Learning Outcomes:

By the end of this training, the attendee will be able to

  • Create and tune a predictive model with one or multiple text columns
  • Explain the differences between TF-IDF and word embedding approaches
  • Locate and explain individual expert settings related to NLP models
  • Using Projects, evaluate added value of text to numeric data when both are available
  • Incorporate additional NLP models and transformers via recipes
  • Evaluate MLI for NLP models


This course assumes 

  • Completion of “Introduction to Driverless AI” or equivalent experience.
  • Completion of “Customizing Driverless AI with Recipes.”
  • Familiarity with statistical or machine learning modeling.

Are you interested in this course? If so, we will email you once this course is available.

Please login to access this poll.