ML101: Reinforcement Learning

Reinforcement Learning a the 3rd area in Machine Learning.  It’s different from Supervised Learning and Unsupervised Learning.

In reinforcement learning, the algorithm gets to choose an action in response to each data point. The learning algorithm also receives a reward signal a short time later, indicating how good the decision was. Based on this, the algorithm modifies its strategy in order to achieve the highest reward. Reinforcement learning is common in robotics, where the set of sensor readings at one point in time is a data point, and the algorithm must choose the robot’s next action. It is also a natural fit for Internet of Things applications.


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