Short Course: Introduction to Machine Learning and Inference

Machine learning, and in particular deep learning, has received a great deal of attention in recent years as it has disrupted many fields of electrical engineering and computer science. The success of deep-learning techniques comes from their ability to solve notoriously difficult classification and regression problems. Much of deep learning's recent successes can be attributed to a virtuous cycle of advances in computing hardware, the availability of huge amounts of labeled data, and development of deeper models. This talk introduces the broad and dynamic field of deep learning for hardware designers. We begin with a brief history and review key innovations that have led to the powerful deep-learning techniques we see today. We will review the different types of learning widely used today with a focus on neural network models for inference applied across a variety of domains. The primary objective of this talk is to help and motivate chip designers to engage in this exciting opportunity and further push the impact of deep learning via hardware-level innovations.