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Вернуться к Deep Neural Networks with PyTorch

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

Оценки: 1,126
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:

201–225 из 251 отзывов о курсе Deep Neural Networks with PyTorch

автор: Roberto G

12 апр. 2020 г.

very practical, lack of theory

автор: Tj

28 апр. 2021 г.

The questions are too simple.

автор: Lemikhov A

19 февр. 2020 г.

No programming assingments

автор: Utkarsh A

9 мар. 2022 г.

G​ood knowledge.

автор: aditta d

4 нояб. 2021 г.

Good lecture...

автор: Mohd N K

14 мая 2020 г.

very practical

автор: Richard B

16 мая 2020 г.


автор: Rafael B

11 февр. 2022 г.

The content of the course is interesting and light and allows for a good basic understanding of the topic. However, the presentation is not good. The automated narration in the videos is often weird and repetitive. The visual presentation is also not great, the colors and diagrams help very little with the understanding of what's happening in the routines (except for the skecthes of the neural networks themselves, which are pretty good). The lab notebooks are riddled with typos. The course would be improved by having a more detailed discussion of what's going on in the code before practice in the labs. Otherwise, I recommend the course for anyone who is starting in the field.

автор: Michael H

21 июня 2020 г.

This course was not to the same standard as some others I've taken on Coursera. I think the concepts would have been very hard to follow if I hadn't already taken the Deep Learning specialization, so it isn't a great conceptual introduction to Deep Learning. That said, it also doesn't deeply explore the nuances of the PyTorch library, or give very much guidance on best practices or how it differs from other popular frameworks like Keras/TensorFlow. The quiz questions are fairly shallow (and often frustratingly ambiguous). Probably the best part of the class are the ungraded lab assignments.

автор: Gasm E M M

14 мар. 2021 г.

I like to feel a human is teaching me, but I felt a robot is teaching instead. Also, many parts of the labs are copied from each other, and that's good, but the sentences and comments are forgotten unchanged and they don't belong to that lab. I preferred if the PowerPoints were designed better. Other than that, I can see that the author tried his best to include everything.

автор: Rajaseharan R

1 нояб. 2021 г.

T​he presenter at times goes too fast and once he's finished talking the slide moves forward before there is time to absorb the material. The slides also contain errors. Should be more throughly reviewed. The labs also contain some bugs. The quizes contain some spelling mistakes and some of the quiz questions are unclear.

автор: Stephan W

6 февр. 2021 г.

Potentially a good course, but due to the very short videos and complete lack of supporting material (not even the slides of the videos), it's hard to follow. You need to watch the videos over and over again and take notes. Not sure why not even the lecture slides are provided.

автор: Julius W

14 мар. 2022 г.

Very theoretical course. You can claim the badge without running any code. The additional honours course consisted of a total of 3 lines of code you had to write. I did not really enjoy this course. It covered a lot of things but was as dry as possible.

автор: Ahssad

11 авг. 2021 г.

It is very fast paced. There are a lot of videos and not enough opportunities to actually reinforce what you have learned in terms of shorts projects. I think at the end of each week, there should be a small project in order to progress.

автор: Chaney O

1 июня 2020 г.

The lectures and quizzes are too short to provide much value. The material could be better condensed. The labs were useful, although at times, it felt like the same material from a prior video. In general, it was a good overview.

автор: Sabrina S

8 мар. 2020 г.

Ok walkthrought of pytorch, a lot of content but slight mismatch between rather basic DS topics and advanced programming skills. Materials need to be reviewed for spelling and grammar, some quiz questions are unclear.

автор: Yi M L

28 окт. 2020 г.

the content is definitely overloaded.. i am blowing.. felt like i went to college again. if cut some of the content it will be much more user friendly to learn.. for an online class prespective

автор: César A C

25 июня 2020 г.

The course is quite complete, but it contains to many things already contained in the previous courses within the Specialization. The final honor part could have been much better.

автор: Massimo B

23 февр. 2022 г.

quality of slides is quite bad and exercises are just a repetition of the class. Nevertheless the basic concepts are explained clearly

автор: Tony D

8 сент. 2020 г.

Very slow and redundant material with previous courses of the "IBM AI Engineering Certificat Professionnel"

автор: Mutlu O

4 авг. 2020 г.

More useful exmples in labs would be helpful to understand the possibilities with the method and tool

автор: Miroslav T

8 июня 2020 г.

quality of videos at the beginning of course are low, fells like the machine is reading it

автор: Benhur O

30 янв. 2020 г.

To focus in the coding but not the underlying structure of the library and how to use it.

автор: Prateeth N

1 июля 2020 г.

Very Basic course. Would have enjoyed more interesting examples in the notebooks

автор: Bhaskar N S

4 апр. 2020 г.

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