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

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.

Course material is great, although it has some errors, as on the video slides as in the notebooks. This should be rectified. Also, the assessments and quizzes should definitely be harder.

Good to dive into Deep Learning and get some PyTorch basics. However, there're sometimes mistakes in the assignments. Also, the explanations can sometimes be a bit confusing.

Amazing course for a beginner in Deep Learning & Pytorch.

I gave 4 stars as I expected it to be more pytorch heavy.

Overall, a really good crafted course.

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.

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

The courses provides basic knowledge, but I wish that it was a bit more advanced and had more challenging assignments.

Some of the courses are quite harsh, but finally come all togheter and there's a light at the end of the tunnel.

the course is good, detailed, and practical, but the shortcoming is the lab quality, need to be imporved

Detailed explanation about pytorch! I expect more examples and harder tests and assignments

generally, the course is well but tasks too easy for "intermediate" level

It would have been better if graded programming assignments were there.

There is a number of errors in the courses and in quiz

less one star due to the many errors I noticed in the

Great Course for beginners in pytorch

good explanation with examples

very practical, lack of theory

No programming assingments

very practical

Challenging

This course was not to the same standard as some others I've taken on Coursera. I think the concepts would have been very hard to follow if I hadn't already taken the Deep Learning specialization, so it isn't a great conceptual introduction to Deep Learning. That said, it also doesn't deeply explore the nuances of the PyTorch library, or give very much guidance on best practices or how it differs from other popular frameworks like Keras/TensorFlow. The quiz questions are fairly shallow (and often frustratingly ambiguous). Probably the best part of the class are the ungraded lab assignments.

The awful text-to-speech voice in the videos and the "We do this.... we do this... we do this..." information dump is poor from a didactic point of view.

The redeeming feature of the course are the labs, but like many of these little courses there's little encouragement to play around with the code.

Potentially a good course, but due to the very short videos and complete lack of supporting material (not even the slides of the videos), it's hard to follow. You need to watch the videos over and over again and take notes. Not sure why not even the lecture slides are provided.

Useful if you are already comfortable with deep learning and you want to learn how to use the (great) pytorch package. If you want to learn about deep learning from scratch, the explanations are not very intuitive and skip over some very interesting features.

The lectures and quizzes are too short to provide much value. The material could be better condensed. The labs were useful, although at times, it felt like the same material from a prior video. In general, it was a good overview.