Have a task you want to schedule? Read on to learn how I automated the weekly collection of fantasy football player data with Github Actions!
Learn how I built an AWS powered alert system that finds the perfect time to go running!
College rankings are a standard input for most students when choosing a school. But to what extent does a college's rank relate to how much a graduate makes 10 years into their career? We'll answer this question by web scraping data from a variety of online sources with R and Python, and then build a model to understand which factors matter most to post-college pay.
Whether predicting daily demand for thousands of products or the number of workers to staff across many distribution centers, generating operational forecasts in parallel is a common task for data scientists. Accordingly, the goal of this post is to outline an approach for creating many forecasts via PySpark.
Portland, Oregon is home to some of the best watering holes in America. With so many places to quaff a West Coast Style IPA or glass of Pinot Noir, choosing which to visit (and in which order) can be a daunting task. To address this question, we'll leverage some classic optimization techniques to minimize the total distance travelled between the top bars in Portland for a truly "optimal" Pub Crawl.
Aaron Rodgers or Tom Brady? Carson Wentz or Drew Brees? Choosing the right Fantasy Football QB each week is challenging. To remove some of the guesswork from the decision-making process, I devised an approach that’s worked well over the past few seasons. Read on to learn more about using the Beta Distribution to pick your weekly starting QB.