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Statistical and decision–theoretic modeling paradigm. By the end of this course, you will have built autonomous agents that efficiently make decisions in stochastic and in adversarial settings. Reasoning and Learning. With this additional machinery your agents will be able to draw inferences in uncertain environments and optimize actions for arbitrary reward structures. Your machine learning algorithms will classify handwritten digits and photographs. Applications for a wide variety of artificial intelligence problems. The techniques you learn will serve as the foundation for further study in any application area you choose to pursue.
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