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CodeSignal

Linear Landscapes of Dimensionality Reduction

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Overview

Unlock the secrets of Linear Discriminant Analysis (LDA) to improve your data's feature selection and enhance model accuracy through hands-on Python exercises.

Syllabus

  • Unit 1: Exploring Linear Discriminant Analysis: Theory to Code
    • Iris Garden Dimensionality Reduction with LDA
    • Reducing to a new dimension
    • Calculating the LDA Transformation Matrix
    • Projecting to the LDA Subspace
  • Unit 2: Exploring Linear Discriminant Analysis with Scikit-Learn
    • Visualizing Iris Dataset with LDA
    • Dimensionality Reduction and Plot Adjustment in LDA
    • Predicting with LDA and Evaluating Accuracy
    • Journey through the Code Nebula with LDA
  • Unit 3: Deciphering Dimensionality Reduction: PCA vs. LDA Techniques and Implementation
    • Dimensionality Reduction Showdown: LDA vs PCA on Iris Dataset
    • Applying PCA and Training the Logistic Regression Model
    • Implementing LDA and PCA in Iris Classification

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