Short Courses

Short Course (SC) | Deep Learning in Statistics

Instructor(s): Annie Qu (UC Irvine), Xiao Wang (Purdue University), Edgar Dobriban (University of Pennsylvania)

Time: Tuesday, November 5, 2024, 1-5 PM, and Wednesday, November 6, 1-5 PM

This short course is for those new to data science and interested in understanding the cutting-edge deep learning models. It is for those who want to become familiar with the core concepts behind deep learning algorithms and their successful applications. It is for those who want to start thinking about how deep learning might be useful in their business or career. This one-day short course will provide a comprehensive overview of deep learning methods from the statistics perspective. Topics include deep feedforward neural networks, convolutional neural networks, deep Boltzmann machine, variational autoencoders, generative adversarial networks, learning theory fundamentals, generalization error bounds for deep neural networks, deep learning in R, an overview of the Keras package. Various application examples will be discussed in detail as well.

Cost: $100. Seats are limited. One may add this short course to his/her registration at any time via the registration form.