Violet Peng
Department of Computer Science
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2.2
Overall Rating
Based on 12 Users
Easiness 2.2 / 5 How easy the class is, 1 being extremely difficult and 5 being easy peasy.
Clarity 2.5 / 5 How clear the class is, 1 being extremely unclear and 5 being very clear.
Workload 2.9 / 5 How much workload the class is, 1 being extremely heavy and 5 being extremely light.
Helpfulness 2.8 / 5 How helpful the class is, 1 being not helpful at all and 5 being extremely helpful.

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Reviews (11)

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Quarter: Winter 2023
Grade: NR
Verified Reviewer This user is a verified UCLA student/alum.
March 25, 2023

Great introduction to NLP and its modern day applications! I learned so much from this course alone. I liked the way the professor explained the material, how it was super engaging and super relevant to how NLP is actually used in the real world. It has even made me consider a career in the NLP/ML field.

The core topic of this course IMO is language models. You start from the very basics (n-grams), and the professor explains step-by-step how language models have evolved over the past few years, culminating at the various transformer models (BERT, GPT).

Grading was very fair and lenient. There were plenty of extra credit opportunities on the projects, and she gave everyone 5 % boost on their midterm and final grades for completing a course survey. The exams themselves were very fair; as long as you understand the lectures, you should be all set.

I also do want to mention the course project, since it allows you to actually have hands-on experience with how researchers are using NLP in the real world. It is a fairly involved group project, but you learn a ton and it could pay off in the future if you choose to pursue something NLP related. That being said, the project takes a LOT longer than one might think, as training the transformer models on the GPUs took forever and the VM environment in which we trained the models kept crashing.

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Verified Reviewer This user is a verified UCLA student/alum.
Quarter: Winter 2023
Grade: NR
March 25, 2023

Great introduction to NLP and its modern day applications! I learned so much from this course alone. I liked the way the professor explained the material, how it was super engaging and super relevant to how NLP is actually used in the real world. It has even made me consider a career in the NLP/ML field.

The core topic of this course IMO is language models. You start from the very basics (n-grams), and the professor explains step-by-step how language models have evolved over the past few years, culminating at the various transformer models (BERT, GPT).

Grading was very fair and lenient. There were plenty of extra credit opportunities on the projects, and she gave everyone 5 % boost on their midterm and final grades for completing a course survey. The exams themselves were very fair; as long as you understand the lectures, you should be all set.

I also do want to mention the course project, since it allows you to actually have hands-on experience with how researchers are using NLP in the real world. It is a fairly involved group project, but you learn a ton and it could pay off in the future if you choose to pursue something NLP related. That being said, the project takes a LOT longer than one might think, as training the transformer models on the GPUs took forever and the VM environment in which we trained the models kept crashing.

Helpful?

0 0 Please log in to provide feedback.
2 of 2
2.2
Overall Rating
Based on 12 Users
Easiness 2.2 / 5 How easy the class is, 1 being extremely difficult and 5 being easy peasy.
Clarity 2.5 / 5 How clear the class is, 1 being extremely unclear and 5 being very clear.
Workload 2.9 / 5 How much workload the class is, 1 being extremely heavy and 5 being extremely light.
Helpfulness 2.8 / 5 How helpful the class is, 1 being not helpful at all and 5 being extremely helpful.

TOP TAGS

There are no relevant tags for this professor yet.

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