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Вернуться к Deep Neural Networks with PyTorch

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

Оценки: 1,159
Рецензии: 256

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.

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251–258 из 258 отзывов о курсе Deep Neural Networks with PyTorch

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.

автор: Xihan L

2 авг. 2022 г.

There are many typos in the quiz; the lab loads slowly.

автор: Walter c

20 июня 2021 г.

The agenda is good but it is not well explained.

автор: Javier J M

22 февр. 2021 г.