On November 9, 2013
This article demonstrates a simple but effective sentiment analysis algorithm built on top of the Naive Bayes classifier I demonstrated in the last ML in JS article. I’ll go over some basic sentiment analysis concepts and then discuss how a Naive Bayes classifier can be modified for sentiment analysis.
On August 18, 2013
I’m fascinated by Morse code. It teaches us about encoding, language, technology, and our ability to learn to communicate in a revolutionary manner. Here’s why I’m learning to speak Morse.
On August 16, 2013
Learning bash scripting ended up turning what used to be a 30 minute manual server build process into a perfect lean, mean, server building machine. Why didn’t I start this earlier?
On March 20, 2013
Today we’re going to solve a simple problem: language detection. Put another way: “given a piece of text, determine if it’s in Spanish, English, or French”.
On January 29, 2013
This is a follow-up to my “Effective teaching is a long-con” article, except in the context of web apps rather than classrooms. In the previous article I basically made the argument that you need to trick people into learning — and that’s how the best teachers do it. Now I’m writing because I recently had an experience where I, myself, was tricked (by a website) into learning.
On November 7, 2012
There are lots of people talking about big data these days. There’s a lot of discussion about how to build apps for “web scale”, and there’s an emphasis on real time apps that collect comprehensive data.
On November 3, 2012
I just spent 48 hours without electricity. I’m not complaining; I could have had it much worse (many people in Staten Island did) and very fortunately nobody I know was hurt or lost their home. But my experience without power got me thinking.
On October 20, 2012
About a year ago I built a Chrome extension called SiteChat — the premise was simple: turn every website into a chatroom. The app was an instant success, and over the following year I watched entire societies emerge and die off inside the bizarre ecosystem that I had created.
On October 15, 2012
Today we’re going to figure out how to find clusters of data points. Let’s say you work at a medical imaging devices company. Imagine you already have a way to identify malignant cells from an image scan, but it would be great to automatically identify the centers of clusters of cells as well. Then a robot could go in with surgical precision and remove the problem!
On October 3, 2012
So far, we’ve modeled everything in this series as particles. Particles are the simplest way to model something physically, because they only have a location in space and don’t have a size or shape. Particles can only translate (move), and can’t rotate.
And while you can do some amazing things just by modeling particles, particles aren’t realistic in the real world. Real objects aren’t just infinitely small dots. Real objects have a size and shape and most importantly, an orientation. Real objects can rotate…