# Dimensionality Reduction

## Overview

Teaching:0 min

Exercises:0 minQuestions

How can we perform unsupervised learning with dimensionality reduction techniques such as PCA and TSNE?

Objectives

Recall that most data is inherently multidimensional

Understand that reducing the number of dimensions can simplify modelling and allow classifications to be performed.

Recall that PCA is a popular technique for dimensionality reduction.

Recall that TSNE is another technique for dimensionality reduction.

Apply PCA and TSNE with Scikit Learn to an example dataset.

Evaluate the relative peformance of PCA and TSNE.

## Key Points

PCA is a dimensionality reduction technique

TSNE is another dimensionality reduction technique