Offered By: IBMSkillsNetwork
Use Kernel PCA To Find Why Are You Poor
Learn to identify patterns in data using Python programming and Data Science. Explore Kernel Principal Component Analysis by uncovering non linear trends, and draw valuable insights from your datasets. It's a powerful extension of traditional PCA that can unravel complex patterns and structures in non-linear data. Maping the data into a higher-dimensional feature space, where non-linear relationships become linear allows KPCA to capture the intricate structures and similarities in the data that may otherwise remain hidden.
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Data Science
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Learn to identify patterns in data using Python programming and Data Science. Explore Kernel Principal Component Analysis by uncovering non linear trends, and draw valuable insights from your datasets. It's a powerful extension of traditional PCA that can unravel complex patterns and structures in non-linear data. Maping the data into a higher-dimensional feature space, where non-linear relationships become linear allows KPCA to capture the intricate structures and similarities in the data that may otherwise remain hidden.
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Certificate
No Certificate Offered
Estimated Effort
30 Minutes
Level
Beginner
Industries
Skills You Will Learn
Data Science, Python
Language
English
Course Code
GPXX05W9EN