Intro to Neural Networks with Applications to Function Approximation — Marko Ristic

Within the past decade, deep learning has become widely utilized in both academic and industry settings. At the heart of deep learning lie neural networks which combine linear algebra and statistics to mimic the learning process which our brains undergo on a daily basis. The beginning of the talk will focus on an elementary introduction to neural networks and their functionalities. The latter portion of the talk will discuss how neural networks can be used for function approximation in the context of parameter estimation.

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