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Process Monitoring And Machine Learning

Instructor:
Peng Wang
578
Credits:
3.0
201
Building:
Robotics & Manufacturing Building
Room:
Rm.309
Semester:
Spring 2023
Start Date:
End Date:
Name:
Process Monitoring And Machine Learning
Requisites:

Prereq: MA 213 and MA 214, EE 421G or ME 310, or instructor permission.

Class Type:
LEC
6:15 pm
7:15 pm
Days:
T

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.

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.

EE