This course teaches how to use Python to perform supervised learning, an essential component of machine learning, and how to build predictive models, tune their parameters, and determine how well they will perform with unseen data—all while using real world datasets.
This course teaches the foundations of deep learning, the major technology trends driving Deep Learning, how to build, train and apply fully connected deep neural networks, how to vectorized neural networks and understanding the key parameters in a neural network's architecture.