Unity

Deep Q-Learning with PyTorch and the Unity ML-Agents Toolkit

Coming soon …

Animating data with Unity

At TRACKTICS we are constantly trying to come up with new ways to visualize the data that our customers acquire with their GPS Performance Trackers. Recently, I created a small prototype, visualizing locations and orientation (yaw angle) time series data in the form of three-dimensional animations using the Unity 3D engine. Here’s a small example: The visualization has been featured in a Report by Stuttgarter Zeitung and might be turned into a new feature for TRACKTIC’s Web App feature - not decided yet, though ;-).

Twitter sentiment analysis

CloudQuake is a university project where I tried to apply real-time sentiment analysis on Twitter streams. Our approach was to first collect data via Amazon Kinesis (which allows for a convenient way to combine data from different sources) and then use Apache Spark Realtime and its MLlib to classify tweets using a simple Naive Bayes classifier trained with publicly available annotations. While the initial idea was to first filter the data for earthquake related tweets and then combine the inferred tweet sentiments with a Long/Short term moving average indicator with the goal to detect whether the mentions of Quake-related tweets allow to detect earthquakes.