Chevron Left
Deep Neural Networks with PyTorch(으)로 돌아가기

IBM 기술 네트워크의 Deep Neural Networks with PyTorch 학습자 리뷰 및 피드백

1,170개의 평가

강좌 소개

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...

최상위 리뷰


2020년 4월 29일

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!!


2020년 5월 15일

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.

필터링 기준:

Deep Neural Networks with PyTorch의 259개 리뷰 중 151~175

교육 기관: Lixy

2021년 8월 10일

easy to understand

교육 기관: VIKAS S

2022년 8월 17일

Excellent Course.

교육 기관: Amir J

2020년 8월 12일

Amazing course!

교육 기관: arash h

2021년 11월 30일

perfect course

교육 기관: CHALLA K S N M S

2020년 9월 21일

awesome course

교육 기관: Philipp A

2022년 7월 28일

G​reat Course

교육 기관: Manh D 1

2022년 5월 9일

really good

교육 기관: Aditya M P

2020년 12월 8일

Good Course

교육 기관: Panos K

2022년 5월 23일


교육 기관: Oyenola P

2022년 7월 6일


교육 기관: Godwin M

2021년 9월 26일


교육 기관: 徐淇

2021년 8월 3일


교육 기관: Abdullaev S

2021년 3월 6일


교육 기관: ASITHA I D

2021년 2월 15일


교육 기관: Marco C

2020년 3월 30일

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.

교육 기관: Peter P

2020년 7월 8일

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.

교육 기관: Benjamin K

2022년 4월 24일

Despite the irritating computer voice and sloppy slides it is a good course. It is less a PyTorch course but an very nice introduction into ML and deep learning in general. Important concepts are introduced without overboarding the material with too much Math.

The labs could be more interesting and challenging. Towards the end the IBM Cloud was not working any more, before it was really convienent to do the labs in the browser. However, there are only a few requirements and anyone with a little Python experience can quickly setup a virtual environment. However, an instruction and a requirements.txt would be nice.

교육 기관: Julien P

2020년 6월 11일

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.

교육 기관: Farhad M

2020년 6월 24일

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.

교육 기관: Felix H

2020년 6월 30일

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).

교육 기관: Mitchell H

2020년 8월 2일

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.

교육 기관: Carlos R

2022년 2월 28일

Exceptional course. The lectures were little monotonous and robotic, I like this courses to be instructed by human speakers, but this did not affect the content of this course, the clarity on the topics and how well it was explained, it helped also to improve my knowledge on computer vision.

Great course.

교육 기관: drygrass

2020년 12월 27일

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.

교육 기관: Josephine J

2021년 7월 19일

Explanation was confusing as time, and text-to-speech lecturer made it harder to engage. Lots of typos and unintuitive phrasing. However, taught useful skills, and all the resources were there to do own thinking/research and eventually understand everything.

교육 기관: bob n

2020년 10월 13일

Concepts presented in nice bite size chunks. Labs help reinforce concepts. BUT, felt like course was just a bunch of pieces with little assembly. Kinda like finding a box of LEGOs (r) with nothing to really build from them.