Qrash Course: Reinforcement Learning 101 & Deep Q Networks in 10 Minutes

This article assumes no prior knowledge in Reinforcement Learning, but it does assume some basic understanding of neural networks. Out of all the different types of Machine Learning fields, the one fascinating me the most is Reinforcement Learning. For those who are less familiar with it -- while Supervised Learning deals with predicting values or classes based on labeled data and Unsupervised Learning deals with clustering and finding relations in unlabeled data, Reinforcement Learning deals with how some arbitrary being (formally referred to as an "Agent") should act and behave in a given environment. The way it is done is by giving the Agent rewards or punishments based on the actions it has performed on different scenarios. One of the first practical Reinforcement Learning methods I learned was Deep Q Networks, and I believe it's an excellent kickstart to this journey.