Teaching

An Introduction to Deep Machine Learning (Fall 2017)

Course: Rice University, ELEC/COMP 576 (formerly 677) (Introductory Graduate-level Course)
Who: Ankit Patel
When: Fall 2017, Wednesdays 2:00 – 4:30pm CST Herring 100. 3 credits.
Website: elec576.rice.edu

Thanks to the development of new learning architectures and algorithms, powerful computing capabilities, and massive training datasets, we have seen in recent years that deep learning systems have redefined the state-of-the-art in object identification, face recognition, and speech recognition. This course will give you a rigorous practical introduction to deep learning, using some of the most popular current frameworks (Google TensorFlow) on some of the most difficult and real-world datasets. Theory will be sprinkled throughout as deemed necessary to enable and support engineering solutions to hard problems.

Seminar in Deep Learning (Spring 2015)

Course: Rice University, ELEC 681
Who: Rich Baraniuk, Ankit Patel, Xaq Pitkow
When: Spring 2015, F 1–3:30. 3 credits.

This course will explore deep learning, multistage machine learning methods that learn representations of complex data. Over the past several years, thanks for the development of new training rules, massive computing capabilities, and enormous training data sets, deep learning systems have redefined the state-of-the-art in object identification, face recognition, and speech recognition. Examples of modern tools include: Facebook’s Deep Face and Google Deep Mind.

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