# 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
Prereqs:
ENGR-6220 Data Architecture

# Past Term Data
Offered
Not Offered
Offered as Cross-Listing Only
No Term Data
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| Spring | Summer | Fall
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| (Session 1) | (Session 2) |
2024 | Machine Learning Frameworks (3c) Rushabh S. Padalia Seats Taken: 5/25 | Machine Learning Frameworks (3c) Rushabh S. Padalia Seats Taken: 2/25 | Machine Learning Frameworks (3c) Rushabh S. Padalia Seats Taken: 2/25
2023 | Machine Learning Frameworks (3c) Rushabh S. Padalia Seats Taken: 4/25 | Machine Learning Frameworks (3c) Rushabh S. Padalia Seats Taken: 1/25 | Machine Learning Frameworks (3c) Rushabh S. Padalia Seats Taken: 3/25
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
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