Machine learning (ML) has been described as the next technological wave to hit humankind, akin to that of electricity. While this is a big claim, we can make certain analogies between the two technologies. For one, you really don't need to understand the inner workings of electricity to use it, and in some ways that applies to ML and many of the more advanced concepts. If you wire up a light the wrong way, it won't work, or you could hurt yourself, and the same analogy applies to machine learning. You still need enough knowledge to call yourself an MLtician or ML practitioner (if you will), and it is the goal of this book to give you that depth of knowledge. Now, the area of ML is broad, so our focus in this book will be to use deep reinforcement learning (DRL) in the form of Unity ML-Agents. DRL is currently a hot topic for developing robotic and simulation agents in many areas, and it is certainly a great addition to the Unity platform.
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