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!
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!
