Отзывы учащихся о курсе Building Deep Learning Models with TensorFlow от партнера IBM

This course is incomplete, and is NOT recommended.

It uses Tensorflow 1, which is outdated now - should be updated to use Tensorflow 2.

It does not provide practice sessions.

Week 5 - Autoencoder - have no audio, no captions, nothing.

There is no final exam to ensure our competence. No labs we need to be graded on.

This is not a worthy Coursera course. It needs to be withdrawn and updated.

The codes need to be updated for TensorFlow 2.0.

course needed to be updated for labs. Now Google moved to Tensorflow 2.0 this year.

Mostly trivial quiz questions and no graded practical work. The certificate is therefore not worth very much.

Good content. A bit too fast on some complex concepts and missing audio for the last lecture but great lecturer.

Teaches more on Deep Learning models but less in TensorFlow

This course is a joke. It's a brief overview of a few types of models. Also there is no sound in half the videos.

Lack of content, quizzes were poor, no sound or transcript on 2 videos. Took about 2 hours total.

I am not sure if no final assessment is a good idea. For the depth of the course it can possibly a major graduation killer but for practical reason you should put that back so people get to be serious with this course.

It is very good to explain concept of Deep Learning by Example , it is so clear, and better understand

It helped me to understand how TensorFlow can be used to build the neural networks

A concise and comprehensive survey of deep learning models. Great labs (which sometimes don't run in IBM Skills Network. Thanks to IBM Watson Studio which came to the rescue in those cases). The labs reinforce concepts and illustrate Tensorflow coding to run the models. Lecturer is very clear and encouraging in tone. Thanks for the course.

Very clear explanation and well organized course. I give 4 stars because videos of Week 5 are missing the audio and subtitles.

Week 5 lecture video no audio

Lab is not update for tensorflow 2

some audios are missing

needs to be updated for tensorflow 2 and the last videos were missing sound

Material from the last 2 weeks aren't comparable to other weeks.

There are 2 main problems with this course:

1 All the codes are for tensorflow version 1 and not 2 which essentially makes them outdated since the new version of tensorflow is quite different from the previous

2 All the explanations are very high level and will leave you with many questions. In short you cna learn as much if not more by watching any youtube videos on each of the topics

In general, the course seems to have been rushed out and the material is ridiculously slim. There is really no reason to take this course. You'll end up frustrated by the simplistic explanations and the fact that you are learning code which won't be relevant in a couple months.

Once again I am so surprised to see a reputable company such as IBM put their name on a product which is frankly embarrassingly bad. There is no way this course would be rated 5 starts by any human being which leads me to believe that they manipulate the scores with fake reviews.

这什么课？即没多少Deep Learning

的内容，也没多少TENSORFLOW的内容？

The videos are well designed and provide concise introduction to the learning models. The codes provided by the instructors are well written and easy to use. However, in order to really understand the codes, one needs to break them down, analyze line by line, etc... which is good. That is my plan for the next weeks.

The speaker has a nice and enthusiastic voice! Not like the one of the pytorch course!!!!!

Deep Learning made me feel that there is a way to build models and classify data so easily and in a skillful way. Amazing course!

Not so often i wish a course would be longer and more in depth I really enjoyed using TF I'll look some other courses about it

This course is the best out of all courses in the specialization, the pace of the speaker was perfect.

the contents are not deep however wide and clearly explained many method/area, good for layman as me!

I would like to thank the lecturer for this fruitful course. I have enjoyed it, Thanks a lot!