TriPeaks Solver
During COVID-19 brain fog, I had just enough mental capacity to play a lot of Microsoft Solitaire games. I found that TriPeaks on master and grandmaster diff...
During COVID-19 brain fog, I had just enough mental capacity to play a lot of Microsoft Solitaire games. I found that TriPeaks on master and grandmaster diff...
This generative art seems less artsy to me, but the idea of generating a maze was interesting. I found the mazegenerator GitHub repo that described the algor...
The generative art journey continues with images produced from machine learning models. In this post, I’ll use k-nearest neighbors to produce two types of ar...
In this post, I’ll generate art based on the idea of a material flowing through an area. Again this was inspired by the the aRtsy package, which has a canvas...
Continuing the series of generative art posts, I liked the look of the canvas_petri() images from the aRtsy package. That led me to this article that describ...
The next stop on my generative art journey took me to the Recaman Sequence. As opposed to many other algorithms, there’s no randomness in this sequence - the...
The inspiration for a series of posts on generative art was a post I read announcing the aRtsy package for producing generative art. A number of the example ...
I was scrolling through the RStudio blog page, and a post by Arthur Holtz caught my attention. He wrote some code to identify what the optimal starting word ...
The following is a subsection of a tutorial I co-authored that I wanted to reproduce here to work out how to get the figures to render properly. Plus, it nev...
The idea for this post started off as essentially a replication of this post but using R and Tidymodels instead of Python.
Continuing with the streak of posts about college football posts, here I finally get into developing some models to predict the winning team and margin of vi...
In a previous post, I created a scatterplot using ggplot2 that displayed college football team logos as the markers using geom_image() from the ggimage packa...
This, to me, is the coolest part. I had no idea this is how some rating systems work, and it’s pretty slick. It’s just one big system of equations that you s...
I’m not a huge football fan. I can’t even remember the last time I watched an NFL game. However, I do sort of follow college football. And being from Oregon,...
GDELT claims to be the largest, most comprehensive, and highest resolution open database of human society ever created.
At work, I needed to create a resolution V (R5) fractional factorial design for use in a study of the relative effectiveness of various modernization programs.
This notebook was written to document the steps and techniques used to achieve a top 2% ranking on Kaggle’s Housing Prices Competition.
As with support vector machines, and as the name implies, classification and regression trees (CART) can be used for either classification or regression task...
Support Vector Regression (SVR) attempts to include as many data points as possible in the area between two lines. The following figure demonstrates this usi...
Recall that if there is a non-linear relationship between predictor and response, we can attempt to transform the predictor using a known function (log, reci...
As we’ve seen in the last few posts, linear models can be successfully applied to many data sets. However, there may be times when even after transforming va...
So far, we have considered designs with just two levels per factor, which is fine for inherently binary factors. However, if our study requires us to include...
So far, we’ve seen regression techniques for continuous and categorical response variables. There is a different form of regression called logistic regressio...
If we have data that includes factors with more than two levels, we have the ability to evaluate non-linear relationships between predictor and response vari...
This post presents methods for finding a balance between under fitting and over fitting a model. Under fitting is when the model is a poor predictor of the r...
In the previous section we considered just one predictor and one response. The linear model can be expanded to include multiple predictors by simply adding t...
There are four assumptions fundamental to linear regression:
The purpose of regression is to describe a relationship that explains one variable (the response, or the “y” variable) based on one or more other variables (...
A couple of weeks ago, I attempted to install the GPU version of TensorFlow and failed miserably. I should have set up a new virtual environment for it, but ...
The DeepMind researchers developed the Double Deep Q-Network after observing that the DQN target network is prone to overestimating Q-Values.
A while back, I found OpenAI’s Gym environments and immediately wanted to try to solve one of their environments. I didn’t really know what I was doing at th...
In a previous post on Q-learning, I demonstrated how to train an agent to play tic-tac-toe. One of the challenges with Q-learning is that it doesn’t scale we...
I recently found the GitHub repository for the Johns Hopkins University Center for Systems Science and Engineering online dashboard, so I thought I’d do a li...
I’ve been reading some books on machine learning, and recently started going through Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow by Au...
Stanford professor Persi Diaconis described an event when a psychologist from the California prison system brought encoded messages obtained from inmates to ...
Just figuring things out.