This is an introductory course on Deep Learning methods with applications to computer vision, natural language processing, biology, financial data, and more. Students will learn foundational knowledge of deep learning algorithms and get practical experience in building neural networks in modern deep learning frameworks. Experience in Python is helpful but not compulsory. We assume students having background in calculus (i.e., taking derivatives) and linear algebra (i.e., matrix multiplication).

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