It’s time again for another episode of “Murderous Deer Machine Learning Mayhem”. Last time, I used a neural network to detect raccoons, since they frequented my backyard more often in the early days. In that post, my preliminary results revealed an accuracy (F1 measure) of approximately 72%. In this …

I’ve been taking pictures for several weeks for my Deer Detector, to keep track of murderous deer. While I haven’t seen as many as I thought I would, I did see a lot of other animals. So, without further delay, here are some of the wildlife photos from …

This is it! This is the post where I talk about the Machine Learning component in my Deer Detector. Have no idea what I’m talking about? Check out my other blog posts here and here for some background information about the project.

Interested in how some machine learning algorithms …

I want to dispel a little bit of the magic behind Machine Learning (awww). In my mind, the name Machine Learning makes it sound like these algorithms are capable of actually understanding the information that you give them, on the same level which a human understands that kittens are cute …

In a previous post, I wrote about how I wanted to use Machine Learning to detect when a deer is present in my back yard, so that I can make sure that no deer-built weapons of mass destruction are constructed in my yard (at least not on my watch!). After …