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Text Analytics in MATLAB

James Wiken, MathWorks
Sarah Palfreyman, MathWorks

Overview

Valuable insights are often buried in large amounts of text data where manual analysis would be unsurmountable to a human. MATLAB® can automate the process effectively and efficiently, letting you interact with and visualize your text data to identify patterns, trends, and complex relationships you could not find otherwise.

Highlights

In this webinar you will learn how to perform text analytics in MATLAB using the Text Analytics Toolbox. The webinar will walk you through two demos of text analytics applications:

  • Topic Modeling with Vehicle Repair Logs for Predictive Maintenance applications.
  • Sentiment analysis with Social Media data for Financial applications.

The demos will teach you the basics of Text Analytics workflows from data import, pre-processing, conversion of text to numeric form, machine learning and deep learning model building.

You will also learn about using the MATLAB Live Editor as a transformative way to create, document and share your text analytics insights with code and output contained in one document along with rich text, figures andequations.  

Who Should Attend

Anyone with text data! Previous knowledge of MATLAB is not required for this webinar.

About the Presenters

James Wiken is an application engineer at MathWorks.

Sarah Palfreyman is the technical marketing lead for the Text Analytics Toolbox.

Recorded: 22 May 2019

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  • Deep Learning Toolbox
  • Statistics and Machine Learning Toolbox

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