This example is drawn from “A Painless Q-Learning Tutorial” at http://mnemstudio.org/path-finding-q-learning-tutorial.htm which explains how to manually calculate iterations using the updating equation for Q-Learning, based on the Bellman Equation (image from https://www.is.uni-freiburg.de/ressourcen/business-analytics/13_reinforcementlearning.pdf): The […]

## Reinforcement Learning: Q-Learning with the Hopping Robot

Overview: Reinforcement learning uses “reward” signals to determine how to navigate through a system in the most valuable way. (I’m particularly interested in the variant of reinforcement learning called “Q-Learning” because the […]

## A Newbie’s Install of Keras & Tensorflow on Windows 10 with R

This weekend, I decided it was time: I was going to update my Python environment and get Keras and Tensorflow installed so I could start doing tutorials (particularly for deep learning) using […]

## Where Do Z-Score Tables Come From? (+ how to make them in R)

Every student learns how to look up areas under the normal curve using Z-Score tables in their first statistics class. But what is less commonly covered, especially in courses where calculus is […]

## Taking a Subset of a Data Frame in R

I just wrote a new chapter for my students describing how to subset a data frame in R. The full text is available at https://docs.google.com/document/d/1K5U11-IKRkxNmitu_lS71Z6uLTQW_fp6QNbOMMwA5J8/edit?usp=sharing but here’s a preview: Let’s load in ChickWeight, […]

## Using xda with googlesheets in R

Want to do a quick, exploratory data analysis in R of your data that’s stored in a spreadsheet on Google Drive? You’re in luck, because now you can use the new xda […]

## Analytic Hierarchy Process (AHP) using preferenceFunction in ahp

Yesterday, I wrote about how to use gluc‘s new ahp package on a simple Tom-Dick-Harry one level decision making problem using Analytic Hierarchy Process (AHP). One of the cool things about that […]