msb-public
/
ML-For-Beginners
mirror of https://github.com/microsoft/ML-For-Beginners.git
1
0
Code Issues Projects Releases Wiki Activity
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
Branches Tags
${ item.name }
Create tag ${ searchTerm }
Create branch ${ searchTerm }
from '8f1770f5af'
${ noResults }
ML-For-Beginners/5-Clustering
History
Jen Looper 8f1770f5af
lesson details on regions 		3 years ago
..
1-Visualize clustering edits 3 years ago
2-K-Means better voronoi image 3 years ago
data re-numbering lesson groups 3 years ago
images re-numbering lesson groups 3 years ago
translations re-numbering lesson groups 3 years ago
README.md lesson details on regions 3 years ago

README.md

Clustering Models for Machine Learning

Regional topic: Clustering models for a Nigerian audience's musical taste 🎧

Nigeria's diverse audience has diverse musical tastes. Using data scraped from Spotify (inspired by this article, let's look at some music popular in Nigeria. This dataset includes data about various songs' 'danceability' score, 'acousticness', loudness, 'speechiness', popularity and energy. It will be interesting to discover patterns in this data!

A turntable

Photo by Marcela Laskoski on Unsplash

In this series of lessons, you will discover new ways to analyze data using Clustering techniques. Clustering is particularly useful when your dataset lacks labels. If it does have labels, then Classification techniques such as those you learned in previous lessons are more useful. But in cases where you are looking to group unlabelled data, clustering is a great way to discover patterns.

Lessons

  1. Introduction to Clustering
  2. K-Means Clustering

Credits

These lessons were written with 🎶 by Jen Looper with helpful reviews by Rishit Dagli Muhammad Sakib Khan Inan.

The Nigerian Songs dataset was sourced from Kaggle as scraped from Spotify.

Useful K-Means examples that aided in creating this lesson include this iris exploration, this introductory notebook, this hypothetical NGO example and