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Volver a Deep Neural Networks with PyTorch

Opiniones y comentarios de aprendices correspondientes a Deep Neural Networks with PyTorch por parte de Habilidades en redes de IBM

1,170 calificaciones

Acerca del Curso

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...

Principales reseñas


29 de abr. de 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!!


15 de may. de 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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226 - 250 de 259 revisiones para Deep Neural Networks with PyTorch

por Tony D

8 de sep. de 2020

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

por Mutlu O

4 de ago. de 2020

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

por Miroslav T

8 de jun. de 2020

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

por Benhur O

30 de ene. de 2020

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

por Chris R

23 de jul. de 2022

There should be slides available for downoad.

The pace of the course was too fast.

por Prateeth N

1 de jul. de 2020

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

por Bhaskar N S

4 de abr. de 2020

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

por Pakawat N

5 de may. de 2020

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

por Liam A

5 de feb. de 2021

OK for beginners, superficial exercises and quizzes.

por Suman S

3 de may. de 2020

The course is too heavy to have just one project.

por 谭皓博

15 de jul. de 2020

A number of mistakes were found in the course.

por Yuping Y

17 de abr. de 2022

It is basically learning by copying code

por Tanmay G

20 de feb. de 2022

G​ood course

por Johannes D

10 de jun. de 2022

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.

por Dan P

13 de may. de 2022

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.

por Will G R

11 de feb. de 2021

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.

por Iain G

2 de abr. de 2020

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.

por Moritz A

13 de jun. de 2022

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.

por Alex D

4 de oct. de 2020

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.

por Victor B

27 de mar. de 2020

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

por Jack C

10 de mar. de 2020

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

por Nicolas B

20 de oct. de 2021

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

por Alessandra B

9 de may. de 2020

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

por sylvain g

19 de mar. de 2020

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

por Karthik R

9 de abr. de 2021

Quite a few errors and lacking flow in the explanations.