Big Data, Small Machine

I was honored to be invited by DevTO to give a talk at their May meetup. The organizers were keen to have someone speak about high-performance machine learning, and I was happy to oblige. The general thesis of the talk is that, for the purposes of machine learning, setting up large compute clusters is wholly unnecessary. Furthermore, it should generally be considered harmful as those efforts are extremely time consuming and detract from solving the actual machine learning problem at hand. To illustrate the point, I showed an online learning approach to binary classification problems using logistic regression with adaptive learning rates.