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In this course you will learn how Principal Component Analysis (PCA) can reduce a variable data set down to variables and barely lose accuracy. You will also learn different type of reducing wide data set, Control, tune and measure the effects of PCA along with Reducing dimensional with classic GBM & GLMNET Variable Selection and ensembling techniques to find the most stable variables.

  • High Dimensionality Data
  • Principle Component Analysis (PCA)
  • Reducing Dimensionality With PCA and GBM modelling
  • Reducing Dimensionality With Variable Selection
  • Reducing Dimensionality With Ensemble Modeling

Duration: 2.5 Hours

Mode: Online Instructor-Led

Fees: $ 25 (Please check website for discount)

Knowledge of R programming

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