Genetic Algorithms Part 3: FanDuel Lineup Example

Genetic Algorithms (GAs) can assist finding optimal or near-optimal combinations. They can significantly reduce the development time and execution time to find a good solution. Continuing from Part 2 which shows a concrete example of how to find the minimum of a quadratic using GAs, this section shows one way to find great fantasy-football lineups using data…… Continue reading Genetic Algorithms Part 3: FanDuel Lineup Example

Stumbling to Package a Django App

Django applications can be packaged individually for reuse. Documentation on how to do so from start to finish seemed either old, sparse, or incomplete. This was my adventure and solution. I’ve used Django to develop a few applications. For one project, I wanted to see how many active users there were interacting with the site.…… Continue reading Stumbling to Package a Django App

Normalizing Football Performances for Better Fantasy Predictions

Normalized scores for NFL teams’ defenses look promising as input to predict game outcomes and fantasy-player performances, but testing is still needed. Working with football statistics, I wanted to evaluate a team’s performance and use the results as input for a LSTM neural network to predict players’ fantasy scores. Basically, the idea is with a better way to…… Continue reading Normalizing Football Performances for Better Fantasy Predictions

Updating the Play-Framework Example

I’ve been learning a bit of Scala recently and I decided to look into one of its most well-known use cases, the Play Framework. This framework, I feel, is similar to Django for Python: a web-application framework that easily integrates database transactions and includes HTML templates. As my only experience in writing a web application…… Continue reading Updating the Play-Framework Example