Machine Learning

Jamie Haddock

Machine Learning

Mathematics department

Jamie Haddock

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from 1 user

Ratings

Bad
Overall 4.0
Good
Hard
Easiness of class 4.0
Easy
Heavy
Workload 4.0
Light
Not Clear
Clarity of professor 3.0
Clear
Not Helpful
Helpfulness of professor 5.0
Helpful
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Grades

Winter 2020
74.2%
61.8%
49.5%
37.1%
24.7%
12.4%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

Fall 2019
34.5%
28.7%
23.0%
17.2%
11.5%
5.7%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

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Reviews

Quarter Taken: Fall 2020
COVID-19 This review was submitted during the COVID-19 pandemic. Your experience may vary.
Submitted Dec. 23, 2020
Grade Received: A

Jamie is undoubtedly a nice person who cares about her students, but this course can be unclear at times. It might be due to the unorganized nature of the textbook, I was always left in confusion throughout the quarter. However, the exams don’t even require you to understand those materials, and a basic understanding of how the algorithms work and their theoretical base should help you ace the exam (mean of 98 in final should demonstrate this point). There is a final project which should be easy as long as you find teammates who are not free riders.

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