ECE 364

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Credit: 3 hours.

Focuses on auto-differentiation tools like PyTorch used with basic machine learning algorithms (linear regression, logistic regression, deep nets, k-means clustering), and extensions in custom methods to fit specific needs. Auto-differentiation tools are essential for data analysis and a solid understanding is increasingly important in many disciplines. In contrast to existing courses which focus on algorithmic and theoretical aspects of Machine Learning, the focus here is on implementation with auto-diff tools.

Prerequisite: MATH 257.

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