In our last post, we implemented our own k-means clustering algorithm in R! Today, we'll explore k-means clustering some more with a Code Lab to see how we can use the algorithm we coded up last time to cluster pixels in an image!
When we shop online, we often get recommendations for other products that are similar to ones we've been looking at. Systems that recommend related products and services are frequently referred to as recommendation systems. In today's Code Lab, we'll code a simple recommendation system using something called cosine similarity!
In our last two posts, we went over how to start making data visualizations in R with ggplot2. Now that we've finished that series, let's work on a Code Lab featuring exploratory data analysis! Today, we’ll be exploring patterns in urban bike share usage...
Now that we’ve had several posts on getting started with coding in R (see Part 1, Part 2, and More Resources) we’re ready to get started with our first Code Lab! In this post, we’ll see how we can estimate pi with dart throwing in R!
In previous posts, we discussed vectors and vector norms in a basic introduction to linear algebra and got some practice working with them in our Code Lab on coding a simple recommendation system in R. Today, we'll follow up on those skills and take a first look at k-means clustering, a machine learning algorithm for clustering!
You probably have your favorite software and tools for writing reports and other text documents but what can we use when we want to write things that involve math equations and symbols? Today's post is a simple guide to getting started with technical writing with LaTeX. LaTeX is a software system that's designed for writing that involves a lot of mathematical equations and symbols.
When we shop online, we often get recommendations for other products that are similar to ones we've been looking at. Systems that recommend related products and services are frequently referred to as recommendation systems. In today's Code Lab, we'll code a simple recommendation system using something called cosine similarity!
Today's post is the first in a new series called Algorithms in the Wild, where we'll discuss case studies featuring machine learning algorithms in some very interesting applications! Our first case study comes from an article in Popular Science on 'How AI could help new Air Force pilots avoid costly mistakes from Popular Science.'
So far, we've been working with single numbers in our posts. Many kinds of data, however, can be represented by matrices. In order to discuss and learn about methods designed for data stored in matrices, today's post is a quick tutorial on getting started with linear algebra in R!
