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Вернуться к Deep Neural Networks with PyTorch

Отзывы учащихся о курсе Deep Neural Networks with PyTorch от партнера IBM

Оценки: 1,131
Рецензии: 250

О курсе

The course will teach you how to develop deep learning models using Pytorch. The course will start with Pytorch's tensors and Automatic differentiation package. Then each section will cover different models starting off with fundamentals such as Linear Regression, and logistic/softmax regression. Followed by Feedforward deep neural networks, the role of different activation functions, normalization and dropout layers. Then Convolutional Neural Networks and Transfer learning will be covered. Finally, several other Deep learning methods will be covered. Learning Outcomes: After completing this course, learners will be able to: • explain and apply their knowledge of Deep Neural Networks and related machine learning methods • know how to use Python libraries such as PyTorch for Deep Learning applications • build Deep Neural Networks using PyTorch...

Лучшие рецензии


29 апр. 2020 г.

An extremely good course for anyone starting to build deep learning models. I am very satisfied at the end of this course as i was able to code models easily using pytorch. Definitely recomended!!


15 мая 2020 г.

This is not a bad course at all. One feedback, however, is making the quizzes longer, and adding difficult questions especially concept-based one in the quiz will be more rewarding and valuable.

Фильтр по:

226–250 из 252 отзывов о курсе Deep Neural Networks with PyTorch

автор: Bhaskar N S

4 апр. 2020 г.

Found it very difficult to follow some of the content and assignments

автор: Pakawat N

5 мая 2020 г.

There are a lot of mistakes in the slides and video but no updates

автор: Liam A

5 февр. 2021 г.

OK for beginners, superficial exercises and quizzes.

автор: Suman S

3 мая 2020 г.

The course is too heavy to have just one project.

автор: 谭皓博

15 июля 2020 г.

A number of mistakes were found in the course.

автор: Yuping Y

17 апр. 2022 г.

It is basically learning by copying code

автор: Tanmay G

20 февр. 2022 г.

G​ood course

автор: Johannes D

10 июня 2022 г.

M​ore "Beginner" than "Intermediate"

F​rom the title i expected a course introducing the depthos of PyTorch for (intermediate) Data Scientists. Instead the course is a shallow introduction to feed forward and convolutional neural networks with a little bit of PyTorch. The course targets beginners who want to learn the basics of ANN / CNN models and learn their first deep learning framework. All others should search for another course.

автор: Dan P

13 мая 2022 г.

This course is an OK introduction to Pytorch and neural networks for beginners, but many better such introductions exist. would be my first recommendation. There are numerous spelling errors, some of which seriously affect the correctness of statements.

The quizzes only test trivial knowledge, and don't go into any real depth.

The total content of the course is maybe 4 hours.

автор: Will G R

11 февр. 2021 г.

Material is good but riddled with grammatical errors and random typos that only make learning more difficult. Also topics are covered at a very minor depth and I often had to look through many additional resources to understand each topic presented.

автор: Iain G

2 апр. 2020 г.

The quizzes are a complete joke. If you're hoping employers will take Coursera certificates seriously, the standard of assessment here is not good enough by a long long way.

автор: Moritz A

13 июня 2022 г.

When doing IBM AI Engineering Course, I will hear content twice here. Explanations could be better. No graded Assignment. Only Quizes with 2-3 question with 2-3 choices.

автор: Alex D

4 окт. 2020 г.

Very technical and math-oriented. Even after completing it, I have no idea how to apply it to the real world. Seems everything is read using a computer voice.

автор: Victor B

27 мар. 2020 г.

I found the course instruction is confusing, sequential and class module should be in different video parts

автор: Jack C

10 мар. 2020 г.

The external tool did not work. I believe there were some maintenance issues. Not good enough.

автор: Nicolas B

20 окт. 2021 г.

T​he course contents are not very interesting, and the quizzes are way too easy.

автор: Alessandra B

9 мая 2020 г.

Not engaging. Had problems opening the notebooks at the beginning of the course

автор: sylvain g

19 мар. 2020 г.

A lot of mistake in the materials.And some labs exercise were unreachable.

автор: Karthik R

9 апр. 2021 г.

Quite a few errors and lacking flow in the explanations.

автор: Dennis T

31 окт. 2020 г.

not indepth enough explaination

автор: Sharad J

29 нояб. 2021 г.

Very high level.

автор: Muzamal A

3 мая 2020 г.

this has been the worst course I have ever seen... the guy is not able to explain as it seems the audience of his course are mathematicians... he makes explanations by showing things and saying numbers but without explaining the principles behind it...

автор: Łukasz C

18 мар. 2020 г.

Overall good course and labs. But labs are so unstable, that it makes this course useless. Out of 4 weeks labs were not accesible for more than a week. Not recommended

автор: Kartik S

26 окт. 2020 г.

the explanation is not in detail. Course Structure is confusing as well. Sometimes the concepts taught are not entirely correct. Overall not a good experience.

автор: Pratik B

12 апр. 2020 г.

Sorry to say, but I really had some high hopes from this course, but this course is not meant to be a part of any specialization.