Data Science for Everyone 5-4 Data Reduction
To reduce the computation time, make data handling more efficient, and prevent curse of dimensionality, we, as a data scientist, need to implement data reduction (i.e., reduce the number of features) by feature selection, feature extraction, etc while retaining as much information as possible.
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Playlist: • Data Science for Everyone
This course is targeted for managers who are not data scientist but need to manage data analytic projects. This is also targeted for managers who want to introduce data-driven management. So, the knowledge provided in this course is both theoretical and pragmatic, but not includes details of mathematics and coding. However, anyone who are beginners in data science are also welcome because this course can provide you with essentials for learning technical aspects of data science.
Takuma Kimura, Ph.D.
Scientist of Organizational Behavior and Business Analytics
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