Features Visualization Solution – Intro to Machine Learning

Features Visualization Solution – Intro to Machine Learning

And, yes, the answer seems to be she likes those. We can’t be absolutely sure, but it looks like she likes the high, soaring intensity songs, and she’s not a big fan of light songs

K-Means Clustering Visualization 3

K-Means Clustering Visualization 3

Now I’m going to show you another set of data that won’t work out quite so perfectly, but you can see how k-means clustering is still. And the type of data that I’ll use in this example is uniform points. This is what uniform points look like. It’s just scattered everywhere. So I wouldn’t look

K-Means Clustering Visualization 2

K-Means Clustering Visualization 2

One of the things that’s immediately apparent once I start assigning my centroids, with these colored regions, is how all the points are going to be associated with one of the centroids, with one of the clusters. So you can see that the blue is probably already in reasonably good shape. I would say that

K-Means Clustering Visualization – Intro to Machine Learning

K-Means Clustering Visualization – Intro to Machine Learning

And I hope you said three, it’s pretty obvious that there should be three centroids here. So let’s add three, one, two, three. So they’re all starting out right next to each other, but we’ll see how as the algorithm progresses, they end up in the right place.

Plots, Outliers, and Justin Timberlake: Data Visualization Part 2: Crash Course Statistics #6

Plots, Outliers, and Justin Timberlake: Data Visualization Part 2: Crash Course Statistics #6

Hi, I’m Adriene Hill and Welcome back to Crash Course Statistics. Last time we left off talking about different data visualizations. The ones we encounter every single day. Whether it’s a chart on the subway telling us the prevalence of heart disease in different age groups, or a histogram on Buzzfeed showing us how many