ECE 59500 - Machine Learning II

Lecture Hours: 3 Credits: 3

This is an experiential learning course.

Counts as:
CMPE Special Content Elective
EE Elective

Experimental Course Offered: Fall 2019

Requisites:
ECE 30200 or equivalent and MA 26500 or equivalent

Catalog Description:
Data-driven machine learning, Probabilistic inference using graphical models, sampling methods, historical perspective for deep learning algorithms and connection to nervous activity, learning with Boltzmann machines, cross-correlation and backpropagation, programming environments, tuning network parameters, generative networks, security aspects of machine learning, reinforcement learning, transfer learning, learning with explicit memory.

Required Text(s): None.

Recommended Text(s):
  1. Deep Learning, 1st Edition, Ian Goodfellow, Yoshua Bengio, and Aaron Courville, MIT Press, 2016, ISBN No. 0262035618.

Engineering Design Content:

Establishment of Objectives and Criteria
Synthesis
Analysis
Construction
Testing
Evaluation

Engineering Design Consideration(s):

Economic