Machine Learning and Deep Learning — Professional Development Continuing Education Course
ASA, Section on Statistical Learning and Data Science
This short course is for those who are new to data science and interested in understanding the cutting-edge machine learning and deep learning models. It is for those who want to become familiar with the core concepts behind these learning algorithms and their successful applications. It is for those who want to start thinking about how machine learning and deep learning might be useful in their research, business or career development. This one-day short course will provide a comprehensive overview of statistical machine learning and deep learning methods. Topics include classical methods as well as modern techniques including basic machine learning tools, supervised and unsupervised learning, deep neural network, computational algorithms and software of deep learning, and various applications in deep learning.
Instructor(s): Annie Qu, UC Irvine; Xiao Wang, Purdue University; Edgar Dobriban, University of Pennsylvania
