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

4.4
stars
858 ratings
193 reviews

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. 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...

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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101 - 125 of 193 Reviews for Deep Neural Networks with PyTorch

By Garrett M

Nov 12, 2020

Excellent course, well put together labs and videos, overall a very dense resource for the topic.

By Vaseekaran V

Oct 23, 2020

Really great intro to PyTorch. Well explained the basics of Deep Learning along with PyTorch.

By Integral S

Aug 9, 2020

this is no doubt THE BEST and the most well thought pytorch and deep learning course so far .

By Andres I C R

Jan 9, 2021

Really good structured with very clear explanation of the math behind the different topics

By Theophile T

Feb 25, 2021

It was my first experience programming in PyTorch and I was amazed.

By Emanuel N

Feb 13, 2021

Gran curso super detallista y explica muy bien los conceptos

By Milad E N

Dec 19, 2020

it goes through neural network and builds it from scratch.

By Quốc H P

Mar 5, 2021

This course is basic and so foundational for begining

By Hasan G

Aug 21, 2020

I have learned good skills for deep neural networks

By Luis C

Aug 17, 2020

best introduction course on the subject.

By Arijit B

Feb 28, 2021

An excellent introduction to PyTorch.

By Oscar A C B

Jun 10, 2020

Excellent! Just what I needed.

By Abdoulaye B K

Nov 6, 2020

The content was on point.

By Amir J

Aug 12, 2020

Amazing course!

By CHALLA K S N M S

Sep 21, 2020

awesome course

By Aditya M P

Dec 8, 2020

Good Course

By Abdullaev S

Mar 6, 2021

Coll!

By ASITHA I D

Feb 15, 2021

Good.

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.

By Julien P

Jun 11, 2020

Here is a list of pros and cons:

Pros: great notebooks and many examples

Cons: the videos are a bit "cheap" (typos and artificial voice) and often miss the intuitions ("To do that, we code like this"). A bit light on the maths. Quizzes are too easy to validate (people may validate with a superficial understanding of what is going on).

Summary: The value of this class resides in the notebooks and in the time your are willing to invest in them.

By Farhad M

Jun 24, 2020

I think it's a good course if you're coming in with the notion of deep learning pretty much clear and are more interested in learning the PyTorch syntax. I'm not sure how useful the course would be in terms of learning ML or DL from scratch. In particular the conceptual slides could be better.

The notebooks are well-prepared. Even though occasional bugs can be found, they aren't much to worry about.

By Felix H

Jun 30, 2020

The course gave a decent and well-structured introduction to PyTorch. However, I would have hoped for less typos (including in the code on the slides), more challenging and instructive quizzes and real exercises (there are instructive labs, but the practice section is usually only a very slight modification of the already given code).

By Mitchell H

Aug 2, 2020

Awesome course for learning the basics/fundamentals of Pytorch. However the labs often would not run some of the more complex or CPU-intensive models, so I would suggest downloading the labs to your local machine. Also could have also used more assignments for hands-on experience, but I would recommend this course.

By drygrass

Dec 27, 2020

Very good fundamental course.

It will be good if real data is used in lab rather than using virtual data.

Also, the notebook's hyperlink of the final assignment isn't work. I can't import the notebook to Watson studio and finish the assignment, please fix it, thank you.