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Avis et commentaires pour d'étudiants pour Deep Neural Networks with PyTorch par IBM

4.4
étoiles
728 évaluations
160 avis

À propos du cours

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...

Meilleurs avis

SY

Apr 30, 2020

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!!

RA

May 16, 2020

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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151 - 161 sur 161 Avis pour Deep Neural Networks with PyTorch

par Victor B

Mar 27, 2020

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

par Octavio L

Aug 28, 2020

Me resultó un tanto tedioso y demasiado largo. Se solapa con contenidos de otros cursos del certificado

par jack c

Mar 10, 2020

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

par Alessandra B

May 10, 2020

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

par sylvain g

Mar 19, 2020

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

par Alistair K

Jun 11, 2020

Utterly abysmal! The lecturer is clearly reading from a script an never actual explains or discusses anything.

The monotonous tone is surely a ML synthesis?

All of the usual typos and code bugs, however even worse than is the fact that some key slides only stay on screen for less than 1 second. A very poor effort on the lecturer's part.

par Mohammad M A

May 03, 2020

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...

par Łukasz C

Mar 18, 2020

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

par Kartik S

Oct 26, 2020

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.

par Pratik B

Apr 12, 2020

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.

par Timur U

Mar 29, 2020

Too many complicated theoretical materials and unclear practical instructions. I have lost motivation for this course.