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image for course Dimensionality Reduction Techniques

Dimensionality Reduction Techniques

Reduce the dimensionality of your dataset by applying feature transformation and feature selection techniques while keeping as much relevant information of the original data as possible.

Course modules

Course Overview

Get an overview of the course.

Lessons:
  • Course Overview
  • Course Example

Feature Transformation Techniques

Transform the variables of a data set to reduce data dimensionality.

Lessons:
  • Feature Transformation
  • Principal Component Analysis (PCA)
  • Factor Analysis

Feature Selection Techniques

Select a subset of variables to reduce the dimensionality of your data set.

Lessons:
  • Feature Selection
  • Feature Ranking Algorithms
  • Built-in Feature Selection
  • Sequential Feature Selection

Conclusion

Learn next steps and give feedback on the course.

Lessons:
  • Additional Resources
  • Survey

Format:Self-paced

Language:English

Language

  • Hands-on exercises with automated feedback
  • Access to MATLAB through your web browser
  • Shareable progress report and course certificate

Machine Learning Onramp

Learn the basics of practical machine learning methods for classification problems.

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