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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 IBM

938 calificaciones
217 reseña

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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176 - 200 de 219 revisiones para Deep Neural Networks with PyTorch

por anupa s

19 de jun. de 2021

Should have more content which covers with examples


28 de jul. de 2020

Great Course for beginners in pytorch

por harshita b

18 de may. de 2020

good explanation with examples

por Roberto G

12 de abr. de 2020

very practical, lack of theory

por Tj

28 de abr. de 2021

The questions are too simple.

por Lemikhov A

19 de feb. de 2020

No programming assingments

por Mohd N K

14 de may. de 2020

very practical

por Richard B

16 de may. de 2020


por Michael H

21 de jun. de 2020

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.

por Gasm E M M

14 de mar. de 2021

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.

por Stephan W

6 de feb. de 2021

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.

por Ahssad

11 de ago. de 2021

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.

por Chaney O

1 de jun. de 2020

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.

por Sabrina S

8 de mar. de 2020

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.

por Yi M L

28 de oct. de 2020

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

por César A C

25 de jun. de 2020

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.

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 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.