Introduction
Google's Artificial Intelligence research group, DeepMind recently released a python API, pySC2 for the popular Real Time Strategy (RTS) computer game, StarCraftII. After successfully conquering the boardgame, Go, with their AlphaGo program, DeepMind has set their sights on the next big challenge for AI systems in attempting to train these systems to learn how to compete with world champions in the increadibly complex world of StarCraft. In this post, we use the pySC2 API to collect gameplay data from replays of human played games with the aim of discoverying some macro elements of the game, such as the different technology progression trees players use. Ultimately, the hope is to build up some intuition on what data is availible from the pySC2 API and how it might be useful in building systems capable of playing the game, but that work will be outside the scope of...
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Introduction
As part of a project course in my second semester, we were tasked with building a system of our chosing that encorporated or showcased any of the Computational Intelligence techniques we learned about in class. For our project, we decided to investigate the application of Recurrent Neural Networks to the task of building a Subreddit recommender system for Reddit users. In this post, I outline some of the implementation details of the final system. A minimal webapp for the final model can be interacted with here, The final research paper for the project can be found here and my collaboraters on the project are Barbara Garza and Suren Oganesian. The github repo for the project can be found here with this jupyter notebook being here.
Model Hypothesis
The goal of the project is to utilize the sequence prediction power of RNN's to...
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