A curated list of academic, popular science, and managerial books on Data Mining, Marketing, and Machine Learning.
Read more »Explore data mining methods and gain insight in to how they work and how to analyze the results.
Read more »Get your hands dirty with data wrangling, writing code, and running algorithms on marketing data.
Read more »As I work on my python script to parse SAS Enterprise Guide projects, I’ve been using git and github to keep track of my changes and keep a stable project while I break things and try to make it better. However, as per my previous post on github, It can be frustrating to work with […]
GitHub is extremely frustrating at times. Especially when you spend more time tweaking your settings rather than writing / committing code. I’m going to walk through a couple situations that I’ve ran into. If you’re looking for a broader, simple tutorial, the git – the simple guide fits that bill nicely as well. Connect an Existing Directory […]
Differences between Machine Learning and Statistics(Quora) (and Econometrics and Bioinformatics and …) What papers every computer scientist should read (Quora). I think reading the fundamental (and accompanying tutorial or implementation) papers on core analysis and computing topics is important. Gaining context in how a technique was developed or what came before it lets you appreciate […]
FastML has a great breakdown of the cutting edge Artificial Intelligence algorithms. Don’t believe the hype.
Essentially that’s what it is. A company acquired by Google developed a fairly general “AI” that can play a series of Atari games. Nature published a video interview with the researchers and it’s pretty interesting. Turns out [3:40] it’s a neural network that takes input as what’s on the game screen and then looks at […]
