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Learn AI with Python · Lesson

Dimensionality Reduction Application

PCA in action with Python.

1

Applying PCA in Python

In this lesson, we’ll apply Principal Component Analysis (PCA) to reduce the dimensionality of a dataset. This helps simplify the dataset while retaining key information.

Dimensionality Reduction Application — illustration 1

2

Dataset Overview

We will use the Iris dataset, which contains measurements of flower species:

  • Features: Sepal length, sepal width, petal length, and petal width.
  • Target: Species (Setosa, Versicolor, Virginica).

All lessons in this course

  1. Introduction to Clustering Algorithms
  2. K-Means Clustering
  3. K-Means Clustering Project
  4. Dimensionality Reduction Basics
  5. Dimensionality Reduction Application
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