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How to Leverage Reinforcement Learning • Phil Winder & Rebecca Nugent

GOTO - The Brightest Minds in Tech

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The Importance of Problem Definition in Data Science

The importance of the problem definition is so crucial for any problem ever on the planet Earth. I don't think it's any more crucial compared to other tools and techniques, because you can start a software project or an ML project and go down the same path. The difference with reinforcement learning is that the problem definition defines whether the problem is doable in the first place. We're going to be taking away the low level, easy decisions that can be automated and letting more complex, let them spend their time on more complex decisions.

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