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YStrano
GitHub Repository: YStrano/DataScience_GA
 Path: blob/master/lessons/lesson_09/README.md
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---
title: Clustering
duration: "3:00"
creator:
    name: Marc Harper
    city: LA
---

Clustering

DS | Lesson 09

LEARNING OBJECTIVES

After this lesson, you will be able to:

  • Understand unsupervised versus supervised learning

  • Apply k-Means and DBSCAN clustering

  • Combine clustering with classification and regression

STUDENT PRE-WORK

Before this lesson, you should already be able to:

  • Use sckit-learn to fit models

  • Use seaborn to create plots

  • Use pandas to load datasets

Instructors: This is a flex lesson and an example lesson on clustering that you are free to use. You will be switching back and forth between the slides and the notebooks. Approximate timing:

  • One hour for k-Means and exercises

  • One hour for DBSCAN and exercises

  • One hour on building models after clustering and silhouette metric

Be sure to copy the slide deck.

BEFORE NEXT CLASS