Step-by-step derivation, explanation, and demystification of the most important equations in reinforcement learning In the previous post we learnt about MDPs and some of the principal components of the Reinforcement Learning framework. In this post, we will build upon that theory and learn about value functions and the Bellman equations. Reward and Return As discussed previously, RL […]
By the end of this two-part series you will know all the basic theory required to understand how reinforcement learning algorithms work. In two posts I will share the most important elements of about 85 pages of reinforcement learning textbook. RL is an extremely useful tool to have in any machine learning practitioners toolkit, and […]
Machine learning is everywhere in translation tasks. After all, the Chinese word ‘mao’ and the English word ‘cat’ carry the same meaning, though in different forms, and machine learning is great at learning underlying patterns and representations. This isn’t much different from taking a picture of a cat, and then sketching the photo. They are […]