Parametric Inference: Karlin-Rubin Theorem

Guide To Linear Regression
Linear regression is one of the first things you should try if you’re modeling a linear relationship (actually, non-linear relationships too!). It’s fairly simple, and probably the first thing to learn when tackling machine learning. At first, linear regression shows up just as a simple equation for a line. In machine learning, the weights are usually represented by a vector θ (in statistics they’re often represented by A and B!).

Image processing tools in python
Here is a list image processing libraries for python along with small code examples wherever possible.

Maxout Networks
Researching for my master thesis I tried to understand the paper by Goodfellow et al. on the Maxout Units. I found it very hard understanding the details and thought a clear explanation in combination with a nice figure would be really helpful. So this is my shot at doing so.

Split Testing for Geniuses
You are sitting at a slot machine with two levers, labeled A and B. When you pull a lever, sometimes a dollar comes out of the slot and sometimes not. The casino tells you that each lever has a fixed chance of giving you a dollar (its success rate) but, of course, they don’t tell you what it is. Since you don’t have any way of distinguishing them to start, you pull lever A and a dollar comes out (Yipee!). What do you do next?

Choosing a Classifier
In order to illustrate the problem of chosing a classification model consider some simulated data, …