Kai-Wei Chang
Department of Computer Science
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5.0
Overall Rating
Based on 1 User
Easiness 3.0 / 5 How easy the class is, 1 being extremely difficult and 5 being easy peasy.
Clarity 4.0 / 5 How clear the class is, 1 being extremely unclear and 5 being very clear.
Workload 2.0 / 5 How much workload the class is, 1 being extremely heavy and 5 being extremely light.
Helpfulness 5.0 / 5 How helpful the class is, 1 being not helpful at all and 5 being extremely helpful.

TOP TAGS

  • Uses Slides
  • Useful Textbooks
  • Tough Tests
  • Participation Matters
  • Has Group Projects
GRADE DISTRIBUTIONS
51.8%
43.2%
34.5%
25.9%
17.3%
8.6%
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.

44.4%
37.0%
29.6%
22.2%
14.8%
7.4%
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.

77.8%
64.8%
51.9%
38.9%
25.9%
13.0%
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.

62.7%
52.2%
41.8%
31.3%
20.9%
10.4%
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.

ENROLLMENT DISTRIBUTIONS
Clear marks

Sorry, no enrollment data is available.

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Reviews (1)

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Quarter: Spring 2022
Grade: A
Verified Reviewer This user is a verified UCLA student/alum.
June 26, 2022

This class is an introduction to NLP and covers tasks such as part-of-speech tagging, word representation, syntactic parsing, semantic parsing, co-reference resolution, machine translation and more. The models and algorithms used for these tasks are a mixture of classical ones (e.g Hidden Markov Models) and modern ones (e.g Transformer neural nets), where the class focuses more on the latter.

Generally, I am very happy with Prof Chang's delivery of this material. The lectures are well-prepared and interactive and are updated regularly to include new concepts, interesting papers, etc. I especially like the quality of the lecture slides, which are almost good enough to learn from on entirely their own.

One issue I had with the class is that it is fairly work-intensive. Here is the list of assignments in the class:
-Weekly quizzes (5 in total)
-1 midterm group project
-1 paper group presentation
-1 final group project
-1 final exam
-Various peer reviews

While there are quite a few, I did like the hands-on nature of these assignments. We could implement a range of different approaches for each project and even had the opportunity to peer-review other students' work. I found the latter especially useful as it gives you a better way to compare and learn than only receiving a grade.

Overall I can really recommend this class to someone interested in NLP. Its material is current and the instructors genuinely want to help you learn about the field.

Helpful?

0 0 Please log in to provide feedback.
Verified Reviewer This user is a verified UCLA student/alum.
Quarter: Spring 2022
Grade: A
June 26, 2022

This class is an introduction to NLP and covers tasks such as part-of-speech tagging, word representation, syntactic parsing, semantic parsing, co-reference resolution, machine translation and more. The models and algorithms used for these tasks are a mixture of classical ones (e.g Hidden Markov Models) and modern ones (e.g Transformer neural nets), where the class focuses more on the latter.

Generally, I am very happy with Prof Chang's delivery of this material. The lectures are well-prepared and interactive and are updated regularly to include new concepts, interesting papers, etc. I especially like the quality of the lecture slides, which are almost good enough to learn from on entirely their own.

One issue I had with the class is that it is fairly work-intensive. Here is the list of assignments in the class:
-Weekly quizzes (5 in total)
-1 midterm group project
-1 paper group presentation
-1 final group project
-1 final exam
-Various peer reviews

While there are quite a few, I did like the hands-on nature of these assignments. We could implement a range of different approaches for each project and even had the opportunity to peer-review other students' work. I found the latter especially useful as it gives you a better way to compare and learn than only receiving a grade.

Overall I can really recommend this class to someone interested in NLP. Its material is current and the instructors genuinely want to help you learn about the field.

Helpful?

0 0 Please log in to provide feedback.
1 of 1
5.0
Overall Rating
Based on 1 User
Easiness 3.0 / 5 How easy the class is, 1 being extremely difficult and 5 being easy peasy.
Clarity 4.0 / 5 How clear the class is, 1 being extremely unclear and 5 being very clear.
Workload 2.0 / 5 How much workload the class is, 1 being extremely heavy and 5 being extremely light.
Helpfulness 5.0 / 5 How helpful the class is, 1 being not helpful at all and 5 being extremely helpful.

TOP TAGS

  • Uses Slides
    (1)
  • Useful Textbooks
    (1)
  • Tough Tests
    (1)
  • Participation Matters
    (1)
  • Has Group Projects
    (1)
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