Machine Learning talk

Here are the “slides” from a talk I gave on machine learning last week. The idea is to give an overview of the different topics and how they fit together. I may end up building on it as I learn about more facets of ML. In case you’re wondering, the slides were created using Hovercraft which is a python tool for creating impress.js slides but authoring them in reStructuredText instead of HTML.

Adventures learning Neural Nets and Python

This documents my efforts to learn both neural networks and, to a certain extent, the Python programming language. I say “to a certain extent” because far from feeling all “yay! I know Python now!” I feel more like “I can use Python 2.7 in certain ways to do certain things… yay?” And what of my understanding of neural nets as a result of this exercise? After battling with my na├»ve implementation of a multi-layer perceptron as described below, I felt I had a pretty visceral understanding of them. Read On →

Welch's T-test in Go

I wrote some code for doing a Welch’s T-Test in Go. You can read up on what a Welch’s t-test is here but in short it’s a significance test for the difference between two treatments (like in an A/B test) where the distributions may have unequal variances. * * * * * * * * * * * ** * *** * ***** * * * *********** -----------------|-----|----------- So if you are doing an A/B test and you have the mean and variance of each treatment, you can get a confidence measure for whether the mean of one is truly higher than the mean of the other. Read On →