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

4.4
645 個評分
145 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

Apr 30, 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 16, 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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76 - Deep Neural Networks with PyTorch 的 100 個評論(共 146 個)

創建者 Philippe G

Mar 10, 2020

Very interesting course. Gives a good introduction to pytorch. My only concern is the quality of the quizzes: It is often limited to 2 very simple questions. This does not allow you to validate that you had a good understanding of the said topic.

創建者 Luca R

Mar 29, 2020

At the beginning, PyTorch framework seems very hard to understand. At the half of course you begin to have a clear vision of the problems. A negative point is the notebook for every topic. I would suggest one for week with everything inside.

創建者 Eric

Jan 20, 2020

Good, thorough course. Does not hold the student to any kind of standard or accountability and quizzes are ridiculously easy to pass.

創建者 Mateo P

Jul 10, 2020

The amount of material was surprisingly extensive and the labs were very useful. The tests were not very good. The videos were OK.

創建者 Andrey G

Jun 17, 2020

The quizzes are way too easy. The videos are OK (read by computer voice except one). The labs, on the other hand, a really nice.

創建者 Paranjape A J

Feb 13, 2020

More graded coding assignments would have been better, but content is good!

創建者 RICARDO H R

Jul 24, 2020

It is a nice course to get you into Pytorch and with some insightful views of how some ML algorithms work but adding to the most upvoted review, the synth voice dialogue sometimes doesn't make sense, the inflections on the speech are weird at times, it spells things that come from a text based explanation rather than someone speaking (things like spelling "I E for -for example- and C N N for convolutional neural network among many, many others)... sometimes the voice is talking about one thing and something else is highlighted on the video, time mismatch...

Many grammar mistakes, stuff left in the examples and quizes that doesn't make sense... definitely needs a redaction and content check.

創建者 Mitchell L

Jul 15, 2020

This course had many flaws including that at the most basic it was riddled with errors, typos, and formatting issues.

Some more specific feedback is that this course seemed overly preoccupied with explaining math concepts or neural net architecture at a high level and glossing over much of the actual pyTorch specific programming.

The organization of the lectures make no sense, with separate lectures and labs for single class and multiclass versions of various models even though the functions all were built to handle multiple dimensions and so there was really no difference. Additionally because the lectures, lab, and quiz used all the same examples this means we would see the exact material presented over and over with no clear pedagogical reason.

Additionally the course seemed overly preoccupied with OOP to the point of replicating the functionality of several built in pyTorch classes obfuscating the actual material with no clear reason given for why we were creating our own version of extant classes.

Lastly, the quizes almost never asked any questions about pyTorch. Most of them were just the most basic questions about comprehending reading code. Things like "if input = 3 how many inputs are there?" or "which option is used for He initialization" and the options are like "He initialization or Xavier"

創建者 sada n

Jan 10, 2020

it is too deep

創建者 A A A

Jul 07, 2020

This course is really good in explaining the concepts and pytorch. Everything was explained in a detailed way, well structured. However, I found the course too segmented. Some lectures, some quizzes, and some labs can be combined. Example for week 1, I think 1.1 (introduction to tensors), 1.2 (1d tensors) and 1.3 (2d tensors) can be combined to single lecture or all 3 lectures be one after another making it appear like it’s together. The 2 labs can be combined into a single notebook. The 2 quizzes can be combined into 1 quiz of maybe 5 or more questions. Similarly, 1.4 (Simple Datasets) and 1.5 (Datasets) can be combined, and so on. I also think that the honours content about batch normalization should be included as part of normal contents. Maybe more advanced concepts can be put up as honours contents.

創建者 Erdem Ş

Jun 17, 2020

even with no mandatory peer graded assignment, for me it was the hardest course to learn in "IBM AI Engineering". So many topics and so many codes to check for each week. i liked it. i believe i will revisit the materials in the future.

創建者 Georgios C

Aug 04, 2020

Great introduction to deep learning with pytorch. It would help if the notebooks in the labs take shorter to run so that the students can experiment with the code and the models.

創建者 Aryal G

Aug 09, 2020

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

創建者 Oscar A C B

Jun 10, 2020

Excellent! Just what I needed.

創建者 amir j

Aug 13, 2020

Amazing course!

創建者 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.

創建者 Peter P

Jul 08, 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.

創建者 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.

創建者 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.

創建者 Fabrizio D

Jul 30, 2020

Positive

-A lot of codes for practicing and learning

-The quizzes are short and focused

Negative

-The videos are too impersonal: it seems that the speaker is just reading the part, after a while I got tired of listening to him.

-Please review the texts: there are too many misspelled words

-Add more line of comments in the codes provided in lab

創建者 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).

創建者 Mitchell H

Aug 02, 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.

創建者 Jesus G

Jun 19, 2020

A nice landing on Pytorch and basic Deep Learning concepts. I liked the collection of code and practical examples. If only, I missed having more difficult practical assignments along the course.

創建者 Theodore G

Jan 11, 2020

Very intensive course. Could do more training labs. But this is definitely a very dense course. Extremely helpful to get started on ML/Deep Learning.

創建者 Jian P

May 10, 2020

Good introduction of PyTorch. There are some minor code errors and inconsistencies in the material but generally not difficult to figure it out.