Fundamentals for Artificial Intelligence and Deep Learning Framework

This class will introduce fundamentals of machine learning techniques and deep dive in cutting edge concepts that enabled neural networks to achieve state of the art performance in many visual, textual, and biomedical problems. Fundamental concepts like feed forward networks, convolution networks, recurrent neural networks, back propagation, loss functions, batch gradient descent, and stochastic optimization will be studied.