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This course introduces students to the fundamental concepts of machine learning and how to implement them in a business. It draws on concepts and results from many fields including statistics, artificial intelligence, control theory, cognitive science and related disciplines. It helps develop algorithms that allow computer programs to automatically improve through experience. Students will learn how to develop and evaluate a concept learning task given hypothesis and labels forming target concepts. They will explore inductive, bayesian and deep learning algorithmic paradigms for business. The focus will be on how these state-of-the-art algorithms and open source software enable future adoption in companies. It will also help with development of business strategies and enable technical planning on new machine learning services and products.
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