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UCL Centre for AI is partnering with DeepMind to deliver a Deep Learning Lecture Series.
Optimization methods are the engines underlying neural networks that enable them to learn from data. In this lecture we will cover the fundamentals of gradient-based optimization methods, and their application to training neural networks. Major topics include gradient descent, momentum methods, 2nd-order methods, and stochastic methods. We will analyze these methods through the interpretive framework of local 2nd-order approximations.