BigDataFr recommends: Reinforcement Learning and AI

[…] If you poled a group of data scientist just a few years back about how many machine learning problem types there are you would almost certainly have gotten a binary response: problem types were clearly divided into supervised and unsupervised.

• Supervised: You’ve got labeled data (clearly defined examples).
• Unsupervised: You’ve got data but it’s not labeled. See if there’s a structure in there.

Summary: At the core of modern AI, particularly robotics, and sequential tasks is Reinforcement Learning. Although RL has been around for many years it has become the third leg of the Machine Learning stool and increasingly important for Data Scientist to know when and how to implement.

Today if you asked that same question you are very likely to find that machine learning problem types are divided into three categories: […]

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By William Vorhies
Source: datasciencecentral.com