Machine Learning Frameworks

ENGR-6221

Students develop predictive models that lead to the least likelihood of unintended variance and build natural language and recommendation engines for common applications such as enhancement engines. Students observe results and tune recommendation models to achieve more accurate predictions and recommendations.

3 credits

Past Term Data

Offered
Not Offered
Offered as Cross-Listing Only
No Term Data
Spring Summer Fall
(Session 1) (Session 2)
2023
Machine Learning Frameworks (3c)
  • Rushabh S. Padalia
Seats Taken: 4/25
Machine Learning Frameworks (3c)
  • Rushabh S. Padalia
Seats Taken: 0/25
Machine Learning Frameworks (3c)
  • Rushabh S. Padalia
Seats Taken: 0/25
2022
Machine Learning Frameworks (3c)
  • Rushabh S. Padalia
Seats Taken: 2/25
Machine Learning Frameworks (3c)
  • Rushabh S. Padalia
Seats Taken: 4/25
Machine Learning Frameworks (3c)
  • Rushabh S. Padalia
Seats Taken: 7/25
2021
Machine Learning Frameworks (3c)
  • Rushabh S. Padalia
Seats Taken: 4/25
Machine Learning Frameworks (3c)
  • Rushabh S. Padalia
Seats Taken: 4/25
Machine Learning Frameworks (3c)
  • Rushabh S. Padalia
Seats Taken: 3/25
2020
Machine Learning Frameworks (3c)
  • Rushabh S. Padalia
Seats Taken: 3/25
Machine Learning Frameworks (3c)
  • Rushabh S. Padalia
Seats Taken: 1/25
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007