Introduction to Machine Learning: Neural Network Architectures

Introduction to neural network based machine learning techniques. Overview includes: Description of deep learning as curve fitting process Development and implementation of leading algorithms for deep learning Overview of back propagation method for enabling optimization Overview of stochastic gradient descent optimization frameworks required for learning Additional lectures can be found at: faculty.washington.edu/kutz/