Introduction to the XML format
Series: Common File Formats
Grid is the very first CSS module created specifically to solve the layout problems we’ve all been hacking our way around for as long as we’ve been making websites.
All you need to know about JSON
Series: Common File Formats
Grid is the very first CSS module created specifically to solve the layout problems we’ve all been hacking our way around for as long as we’ve been making websites.
A deep dive into partitioning around medoids
Series: Kmeans and Its Variants
In this final article in my mini-series on k-means and its variants, I will talk about the k-medoids algorithm, also commonly called partitioning around medoids (PAM). It has the beauty of being basically deterministic and find very good solutions reliably.
How to cluster noisy data sets
Series: Kmeans and Its Variants
Real-world data sets often come with many outliers that you might not be able to remove completely during the data cleanup phase. If you have run into this problem, I want to introduce you to the k-medians algorithm. By using the median instead of the mean, and using a more robust dissimilarity metric, it is much less sensitive to outliers.
The k-means++ algorithm to kick start your initialization
Series: Kmeans and Its Variants
k-means is a very simple and ubiquitous clustering algorithm. But quite often it does not work on your problem, for example because the initialization is bad. Fortunately, there is an improved initialization method, k-means++, which can help to alleviate this problem.
A simple framework for performance metrics
The list of performance metrics is seemingly never-ending. Especially if you are new to data science, you can easily feel stranded in an ocean of choices. Learn how they connect to each other and how you can use it to choose the best metric for your problem and model.
The Dendrite Nanomap
Synapses are at the center of neuronal communication, yet they are incredibly difficult to study. During my PhD I created the a comprehensive, quantitative model of the postsynapse at the nanometer scale