Embodying intelligent behavior

During the course Embodying intelligent behavior in social context, I researched explainable machine learning (ML) and wrote a paper describing the design of an implementation of explainable ML in an app for memory training for the elderly. There was a focus on the theoretical aspect of ML, but my group also made significant technological efforts by implementing a reinforcement (Q-learning) model from scratch.

This course was invaluable in teaching me both the theories and practical skills to think about and work with explainable ML. I was able to gain a comprehensive understanding of how explainable ML systems can be designed and the potential implications of such systems in our society. Furthermore, I was exposed to the mathematics behind reinforcement learning algorithms, which gave me a much deeper appreciation of the inner workings of machine learning systems.