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

4.4
étoiles
720 évaluations
157 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
29 avr. 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
15 mai 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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51 - 75 sur 157 Avis pour Deep Neural Networks with PyTorch

par Suan S A C

8 avr. 2020

I really enjoy this course!!!

par Gordon P R

30 mars 2020

Good introduction to pytorch.

par Shreya D

2 mai 2020

very well structured course.

par Irfan S

31 mai 2020

Labs were detailed one.

par Samira G

30 mai 2020

Outstanding course...

par David S

29 mars 2020

Fantastic explanation

par Julien V

3 juin 2020

Great course !

par Aditya G P

28 avr. 2020

Awesome course

par Marvin L

6 févr. 2020

It was Good !!

par Dishit P

27 avr. 2020

best course

par Branly L

8 avr. 2020

Nice..!!

par Pietro D

3 janv. 2020

The course is interesting and well organized but the quiz are not challenging and full of typos.

par Juho H

6 mai 2020

This course is difficult to rate as a learning experience. There are some very good parts yet there is also some very poor material. I would say that if you are already very familiar with machine learning and Python BEFORE taking this course, you can still draw some useful learnings on how PyTorch can be applied to various problems, and how to create convolutional neural networks with it; but if you are uncertain about some of the key concepts, this course may only end up making things worse for you.

To give an idea of the problems, there are issues like:

- When explaining the train/validation/test data logic and how validation data can be used to prevent overfitting, the videos keep calling training data test data.

- Pytorch is used for some really fancy stuff like defining functions and datasets, but then those functions are not parametrized in any sensible way – meaning if you want to compare loss functions from two different initialisations of the model weights, you are expected to define a new function so you can just change the variable “LOSS” to “LOSS2”, rather than just passing the loss function as a parameter or just initializing or returning it. Given the Pytorch logic is not your regular Python stuff, a best practice should be provided – it is definitely not writing a new function every time.

So be warned: if you know what you are doing, and simply want to learn how to do it with Pytorch, this may still be a decent course for you, just ignore all the stuff where the instructors make mistakes (and they are plenty, also in incorrect quiz answers). But if you feel at all uncertain, I suggest you hone your machine learning skills elsewhere, because otherwise this course will leave you totally confounded on even the very basics of machine learning.

On the upside then, you learn Pytorch through repetition. In the beginning, the logic appears very intimidating, but then you gradually learn the logic and you can do some very impressive stuff quite easily in the end. Be prepared for the amount of repetition, however - first the stuff is shown on a video, then you run the exactly same stuff in a lab, and unfortunately the Skills Lab is not at all efficient for some of the stuff - I ended up downloading the notebooks and using them on my Watson Studio account for much faster performance.

par Konstantin S

24 févr. 2020

Poorly prepared materials, awful quiz modules, lots of mistakes

par Amar S

22 août 2020

I am very disappointed with the quality of the course materials. The videos are recorded with what sounds like a text to speech system or a voice over done by a voice actor who does not really understand the subject matter and lacks personality.

It's hard to understand as it all runs at the same pace and there isn't sufficient time given to specific concepts that may take a shorter or a longer time to sink in depending on their complexity. It's just a constant speed monologue without any real feeling or passion in the subject matter.

par Oussama B

26 févr. 2020

Bad !!!!! Many mistakes, questions too easy !!! I am really disapointed

par Karishma D

21 juil. 2020

The right level of detail so that you can dive in.

I wish there had been a week to cover RNNs as well though, in particular the best way to handle variable length sequences for RNNs :)

par Surya P S

27 juil. 2020

Wonderful course!!! Best among all the courses under AI Engineer Certificate by IBM. Deep learning always haunted me with the maths involved but now I get a very good start with this.

par Divyansh C

7 juil. 2020

I really appreciate this course. Its really amazing course and if you are a beginner in Deep Learning and want to use and learn Pytorch then this course is really good to start.

par Diego D

12 juil. 2020

Excellent Course. I love the way the course was presented. There were a lot of practical and visual examples explaining each module. It is highly recommended!

par okta f s

18 juin 2020

By this course I can understand the basic concept for building neural network or deep lerning model using PyTorch. Very Good course to beginner.

par Zhenzhou Z

1 juil. 2020

It would be better to add a section explaining the experiment code of the famous paper.

par Siladittya M

23 juil. 2020

Quiz questions are very easy. Graded Programming Assignments would have been better.

par Sofyan T

22 juil. 2020

clear instruction, great ilustration and process description. Thank you so much

par AYUSH K

5 juil. 2020

incredible course covering from basics to a satisfaction level