Abstract: In the previous talk, we looked at Reinforcement Learning in general, and discussed Q-learning. This time we will look at DQN in some depth, which combines deep learning with Q-learning. We will look at the base algorithm and some implementation issues. We will look at some important variants of DQN.
Speaker Bio: Robin Chauhan has a longstanding interest in AI and machine learning theory and practice. He has applied AI to venture capital, fintech fraud, transportation, and environmental engineering. He holds a BASc in Computer Engineering from University of Waterloo.
A meetup for people who want to LEARN Data Science as a group. Taking online courses together. Reading books together. Etc. Also with some hands-on workshops taught by 'experts'. It's also a place where you can ask others questions and for help.