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Learn Unity ML-Agents - Fundamentals of Unity Machine Learning by Micheal Lanham

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But what does it do?

At their core, neural networks are just really good, nonlinear function approximators, which means they are just good at solving equations. If you think back to our first example in Chapter 1, Introducing Machine Learning and ML-Agents, we used a simple linear ML algorithm called linear regression to predict cannon velocities. While we were able to estimate things reasonably well with a linear method, what we really needed was a nonlinear solution. While there are a variety of other nonlinear methods we could use, neural networks provide us the ability to develop more generalized and better-fitting solutions, without all the math.

For us, this means neural networks—or deep networks, as we will call them—will be used as ...

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