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Learner Reviews & Feedback for Deep Neural Networks with PyTorch by IBM

4.4
stars
1,602 ratings

About the Course

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....

Top reviews

SY

Apr 29, 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 15, 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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201 - 225 of 352 Reviews for Deep Neural Networks with PyTorch

By ASHISH K P 2

•

Feb 3, 2023

yeah, it was good experiance thank you coursera team

By mehran k

•

Nov 14, 2023

I just can say, my sincere thanks goes to your team

By chibuike j

•

Aug 6, 2023

challanging, but helps alot. So much were explained

By Chuan K

•

Jun 4, 2023

Great and helpful to understand this field

By P A R

•

Jan 5, 2023

it is the best course that i have taken

By Leonardo M

•

Apr 1, 2024

Excellent for beginners. I recommend.

By Esam M O

•

Sep 30, 2023

Great course and great instructor

By Wajeeh U H

•

Feb 11, 2024

Had a great learning experience

By Bilal K

•

Feb 6, 2023

Excellent course for learning.

By Vasamsetti S S H

•

Apr 20, 2023

Perfect.Nice Explaination

By Pierre R

•

May 18, 2023

good overview of pytorch

By Elham S

•

Mar 3, 2023

very good. thank you

By Ramiz U H

•

Jul 28, 2023

Great experience !

By Jordi T G

•

Apr 7, 2023

Very nice course!

By milad k

•

May 29, 2023

awesome course

By Muhammad Q

•

Oct 5, 2023

V good course

By Sabeur M

•

May 13, 2023

Great Course

By Naina M

•

Feb 7, 2024

it was good

By 23315016 V A

•

Apr 8, 2024

tres bien

By José M

•

Mar 9, 2023

Excelente

By 01fe21bec413

•

May 11, 2024

Good

By Boong P P

•

Dec 23, 2023

good

By EC-199 S

•

Dec 10, 2022

nice

By Marco C

•

Mar 30, 2020

The course is good and has a nice mixture of theory and practice, which is essential for mastering complex concepts. However, I do have a few observations about the course quality:

- Several of the slides in the presentations and even the labs have a lot of grammar mistakes.

- The theory is often rushed in the lectures. The course would greatly benefit from a more careful analysis of the maths behind each concept.

-In its effort to make the concepts easier to grasp, the lectures keep using coloured boxes to replace mathematical terms. I found that to be more confusing, they use far too many colours and are too liberal with their use.

-Lastly, the labs completely broke down in the second half of the course. My understanding from the course staff is that an upgrade was made on the backend which did not go well and thus caused those issues. They should have several backup plans for those occurrences, starting with having the labs available for download so that the students can do them offline.

Overall I'm happy with the course and would cautiously recommend it, given the above shortcomings.

By Peter P

•

Jul 8, 2020

The course was fantastic for someone like me. I already knew all the math, and the course gave deep exposure to the needed Python routines and classes. The labs really help cement the knowledge.

Only drawback is that it went a bit too slow for me (NN with one input, NN with two inputs, NN with one output, NN with two outputs, etc.), but others might disagree.

I'm giving it a four because there were so many typos and mistakes (i.e. the gradient is perpendicular to countour lines, not parallel), lots of mispellings and wrong data on the slides and the speaker sounded like a computer (he pronounced the variable idx as "one-dx" - huh? I understand that there's going to be mistakes, but this is an one online course made for many people, and you'd expect that kind of stuff to be corrected over time since it is being repeatedly delivered.

But - it was a great course and I highly recommend taking it.