10 Mar 2018 ·
15 min read
I recently released a machine learning stock prediction project on GitHub, unimaginatively named MachineLearningStocks. It is a project that I’ve put quite a lot of time into, and is in fact a simplified version of a system that I’ve been using to live trade. This post doesn’t really offer anything on top of the existing readme, but I figured it would be good to have a copy (with some minor changes) here as well.
28 Dec 2017 ·
11 min read
In this post, I present my opinion to a question I frequently get asked: how do I get started with machine learning?
10 Oct 2017 ·
12 min read
Decision trees make for pretty vanilla classifiers: they do an unspectacular job with most machine learning tasks, and you’d be forgiven for overlooking them when deciding on a classification algorithm. But decision trees happen to be the cornerstone of a powerful class of learning algorithms: gradient tree boosting methods. I will try to elucidate the (short) history of gradient tree boosting, starting with the pioneering implementation of boosted trees and ending with the state-of-the-art. I’m afraid there will be a hearty amount of mathematics, but it is really a very intuitive topic at its core.