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This course aims at introducing the students to machine learning (ML) techniques used for various signal processing applications. There will be spectral processing techniques for analysis and transformation of audio signals. The lectures will focus on mathematical principles, and there will be coding based assignments for implementation. Prior exposure to ML is not required. The course will be focused on applications in audio signal processing, and the theory will be tailored towards that end.

This course covers complexity results for first order and related optimization algorithms. Such algorithms are widely applied to numerous problems in machine learning, signal processing, communications, etc. and have witnessed a surge in popularity since the advent of Big Data around 2005. Wherever possible, we will attempt to follow a generic template for the proofs, thereby unifying a large number of results in the literature.