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Deep Reinforcement Learning Hands-On by Maxim Lapan

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RL formalisms and relations

Every scientific and engineering field has its own assumptions and limitations. In the previous section, we discussed supervised learning, in which such assumptions are the knowledge of input-output pairs. No labels for your data? Sorry, you need to figure out how to obtain labels or try to use some other theory. It doesn't make supervised learning good or bad, it just makes it inapplicable to your problem. It's important to know and understand those play rules for various methods, as it can save you tons of time in advance. However, we know there are many examples of practical and theoretical breakthroughs, when somebody tried to challenge the rules in a creative way. To do this you should first of all know the limitations. ...

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