MFS 578 - PROCESS MONITORING AND MACHINE LEARNING

Stanley and Karen Pigman College of Engineering

Credits: 3

This course will include two major parts: machine learning theories and applications. Machine learning theories will cover legacy techniques (e.g., support vector machine, Bayesian inference) and then go deeper into deep learning (convolutional and recurrent neural network). The application part will cover some practical studies on how can we leverage the machine learning techniques to analyze the data collected from factory floors. Also, programming of the machine learning techniques (e.g., Python) will be covered in the class as well.

Prerequisite(s):
Prereq: MA 213 and MA 214, EE 421G or ME 310, or instructor permission.
Approved for Distance Learning.
Crosslisted with: ME 578, EE 578