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學生對 IBM 提供的 Deep Neural Networks with PyTorch 的評價和反饋

4.4
1,018 個評分
226 條評論

課程概述

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...

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SY
2020年4月29日

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
2020年5月15日

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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126 - Deep Neural Networks with PyTorch 的 150 個評論(共 227 個)

創建者 Sourabh K

2021年6月26日

One of the best course in the IBM AI Engineer Specialization !

創建者 Emanuel N

2021年2月13日

Gran curso super detallista y explica muy bien los conceptos

創建者 Milad E N

2020年12月19日

it goes through neural network and builds it from scratch.

創建者 Huy P

2021年3月5日

This course is basic and so foundational for begining

創建者 Hasan G

2020年8月21日

I have learned good skills for deep neural networks

創建者 林靖翰

2021年7月30日

The teaching of this course is clear and complete

創建者 Krittamet K

2021年5月23日

Much more understand how deep neural works!!

創建者 Luis C

2020年8月17日

best introduction course on the subject.

創建者 ilovecats

2021年4月29日

awesome, this is like 2 courses in one

創建者 Arijit B

2021年2月28日

An excellent introduction to PyTorch.

創建者 Oscar A C B

2020年6月10日

Excellent! Just what I needed.

創建者 Abdoulaye B K

2020年11月6日

The content was on point.

創建者 Lixy

2021年8月10日

easy to understand

創建者 Amir J

2020年8月12日

Amazing course!

創建者 arash h

2021年11月30日

perfect course

創建者 CHALLA K S N M S

2020年9月21日

awesome course

創建者 Aditya M P

2020年12月8日

Good Course

創建者 Godwin M

2021年9月26日

AWESOME

創建者 徐淇

2021年8月3日

good!

創建者 Abdullaev S

2021年3月6日

Coll!

創建者 ASITHA I D

2021年2月15日

Good.

創建者 Marco C

2020年3月30日

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.

創建者 Peter P

2020年7月8日

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.

創建者 Julien P

2020年6月11日

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.

創建者 Farhad M

2020年6月24日

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.