What is reinforcement learning?

Our journey begins with understanding what reinforcement learning is about. Those who are familiar with machine learning may be aware of several learning paradigms, namely supervised learning and unsupervised learning. In supervised learning, a machine learning model has a supervisor that gives the ground truth for every data point. The model learns by minimizing the distance between its own prediction and the ground truth. The dataset is thus required to have an annotation for each data point, for example, each image of a dog and a cat would have its respective label. In unsupervised learning, the model does not have access to the ground truths of the data and thus has to learn about the distribution and patterns ...

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