Lara Dolecek
Department of Electrical Engineering
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4.0
Overall Rating
Based on 2 Users
Easiness 2.5 / 5 How easy the class is, 1 being extremely difficult and 5 being easy peasy.
Clarity 3.5 / 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 4.0 / 5 How helpful the class is, 1 being not helpful at all and 5 being extremely helpful.

TOP TAGS

  • Tolerates Tardiness
  • Useful Textbooks
GRADE DISTRIBUTIONS
41.1%
34.2%
27.4%
20.5%
13.7%
6.8%
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.

30.9%
25.7%
20.6%
15.4%
10.3%
5.1%
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 (2)

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Quarter: Spring 2020
Grade: A+
COVID-19 This review was submitted during the COVID-19 pandemic. Your experience may vary.
June 19, 2020

Note: Class taken remotely during COVID-19.
Professor Dolecek is a truly accommodating professor and I think everyone in the class can tell that she truly cares for her students. Right from the very first day, she had established plans on how we will take the midterm and final which were both 24hrs open book open notes. It was nice to know what we were getting into.
Her lectures were clear most of the time and they were all through pre-recorded videos. It was nice that we could go at them at our own pace. If we had question, there was a forum where we can ask them and both the professor and the TAs answered in a timely manner. I felt like I was able to learn a lot from her class, and the hws really help reinforced concepts taught in class. It is important to note that her class is VERY MATH(linear algebra)-HEAVY which was kinda expected given ML is heavily based on math. A lot of the exam questions and homework questions are math proofs, and every question involved either linear algebra, multivariate gaussian, or multivariate differentiations in some form. You will come out of this class having not only understand basic ML concepts but also how all the math works behind the scene.
Her HWs are difficult but doable. Once you do them, you can be sure that you understand the lecture materials and will be well prepared for her assessments.
I strongly suggest taking M146 with Professor Dolecek as you will for sure learn a lot from her and have a decent experience :)

Helpful?

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Quarter: Spring 2019
Grade: A
Verified Reviewer This user is a verified UCLA student/alum.
Aug. 11, 2019

This was the first time Professor Doleček taught Machine Learning. Having taken Electrical and Computer Engineering 131A (Probability) with Professor Doleček, this class was a minor disappointment. Especially near the beginning of the class, the lectures were fairly unclear – to this day, I don't have the strongest grasp of Bayesian statistical terms (prior, posterior, likelihood) that the student is expected to know for the rest of the class. However, her teaching settled down a bit after a few weeks, but it somehow never quite seemed to reach the clarity of her 131A lectures.

Compared to 131A, this class was around the same difficulty level. The homework had a lot of strenuous calculus in it, but you do learn a lot if you were to put in the effort to do them. (Apparently the TAs explain them in some level of detail, but I found it difficult to understand them so chose not to go to discussions most of the time. They did post notes though, which I didn't find out till week 7 or so. Oops.)

On the other hand, the exams were a few orders of magnitude easier. Perhaps it's just because it was the first time Professor Doleček taught this class, but the exams were pretty much the same things as homework problems, with some conceptual questions mixed in.

Also check out my review for course 131A: https://bruinwalk.com/professors/lara-dolecek/ec-engr-131a/, and search for “one of the hardest classes.”

Helpful?

1 0 Please log in to provide feedback.
COVID-19 This review was submitted during the COVID-19 pandemic. Your experience may vary.
Quarter: Spring 2020
Grade: A+
June 19, 2020

Note: Class taken remotely during COVID-19.
Professor Dolecek is a truly accommodating professor and I think everyone in the class can tell that she truly cares for her students. Right from the very first day, she had established plans on how we will take the midterm and final which were both 24hrs open book open notes. It was nice to know what we were getting into.
Her lectures were clear most of the time and they were all through pre-recorded videos. It was nice that we could go at them at our own pace. If we had question, there was a forum where we can ask them and both the professor and the TAs answered in a timely manner. I felt like I was able to learn a lot from her class, and the hws really help reinforced concepts taught in class. It is important to note that her class is VERY MATH(linear algebra)-HEAVY which was kinda expected given ML is heavily based on math. A lot of the exam questions and homework questions are math proofs, and every question involved either linear algebra, multivariate gaussian, or multivariate differentiations in some form. You will come out of this class having not only understand basic ML concepts but also how all the math works behind the scene.
Her HWs are difficult but doable. Once you do them, you can be sure that you understand the lecture materials and will be well prepared for her assessments.
I strongly suggest taking M146 with Professor Dolecek as you will for sure learn a lot from her and have a decent experience :)

Helpful?

1 0 Please log in to provide feedback.
Verified Reviewer This user is a verified UCLA student/alum.
Quarter: Spring 2019
Grade: A
Aug. 11, 2019

This was the first time Professor Doleček taught Machine Learning. Having taken Electrical and Computer Engineering 131A (Probability) with Professor Doleček, this class was a minor disappointment. Especially near the beginning of the class, the lectures were fairly unclear – to this day, I don't have the strongest grasp of Bayesian statistical terms (prior, posterior, likelihood) that the student is expected to know for the rest of the class. However, her teaching settled down a bit after a few weeks, but it somehow never quite seemed to reach the clarity of her 131A lectures.

Compared to 131A, this class was around the same difficulty level. The homework had a lot of strenuous calculus in it, but you do learn a lot if you were to put in the effort to do them. (Apparently the TAs explain them in some level of detail, but I found it difficult to understand them so chose not to go to discussions most of the time. They did post notes though, which I didn't find out till week 7 or so. Oops.)

On the other hand, the exams were a few orders of magnitude easier. Perhaps it's just because it was the first time Professor Doleček taught this class, but the exams were pretty much the same things as homework problems, with some conceptual questions mixed in.

Also check out my review for course 131A: https://bruinwalk.com/professors/lara-dolecek/ec-engr-131a/, and search for “one of the hardest classes.”

Helpful?

1 0 Please log in to provide feedback.
1 of 1
4.0
Overall Rating
Based on 2 Users
Easiness 2.5 / 5 How easy the class is, 1 being extremely difficult and 5 being easy peasy.
Clarity 3.5 / 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 4.0 / 5 How helpful the class is, 1 being not helpful at all and 5 being extremely helpful.

TOP TAGS

  • Tolerates Tardiness
    (1)
  • Useful Textbooks
    (1)
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