This course is very practical and interesting.\n\nI enjoyed the excitement I got along the way.\n\nIt was modeled to make you pass as long as you want to pass.\n\nThank you Laurence and Andrew.
No doubt, the team of Deeplearning.AI is building best learning resources. We would love to get more and more resources for easy way learning from DeepLearning.AI Team.\n\nThanks to all.
By Stéphane D•
Laurence Moronay is really a great teacher and the course is very interesting and pleasant.
I Have removed 2 stars for the time wasted trying to make the examples and exercises provided with the course work :
=> Mobilenet Model version not compliant with the grader
=> A lot of WebGL issues (solved by setting backend parameter to "cpu")
Suggestion : report these issues during training to avoid hours spent on the forum
We can see people who already had these problems months ago and nothing is done to improve things
By Francesco B•
The course is good and interesting. It gives an overall idea on how to embed TF models in js. As in other courses of this specialisation, it is not an in-depth course but rather a fast-forward one: in my opinion this is good if you are not interested that much in these topics, not enough if you want to go deep. Nevertheless, contents are still comprehensible and concepts quite clearly explained. However, one might find more than one difficulties when trying to implement something by themselves.
By Tryggvi E•
Mildly interesting to see this work can be done in JS, but from my viewpoint: Why? I already can do it in Python... I am only stepping through this course on my way to the third and fourth courses in this specialization.
By Chris K•
Quizzes are based on syntax and spelling, which feels like a waste of time. Questions should be more about concepts. Examples are pretty basic.
By Igor M•
Too basic. All exercises are copy paste from the shown examples. All 4 weeks you can complete in just 1.
By Simon O•
Not as good as previous deep learning courses. The exams could have been a bit harder.
By check l•
Explain the accuracy requirements for the assignments
By Abungu B O•
ohh the last assignment on rock paper and scissors
By Stephan S•
A lot of coding and only a few ML/AI concepts.
By jeff s•
The intent to teach DL application in the browser is well scoped. I would suggest more background reading including fundamentals and articles outlining state of the art (challenges and approaches - successful and not), and then additional reference material surrounding related areas such as execution on the edge device. But nothing should excuse coursera or the teachers from technical difficulty experienced by many (dozens of students) with grading. Who is at fault? You wasted my time. And you let dozens of students collide head-on without warning into this problem. You should, at the very least admit to your failure and more importantly compensate me one full course at no charge. Without compensation, i see no reason to trust you. Equally important, Coursera is an off-line teach ing system. I make mistakes. I get so little feedback, your system blocks my learning. There is incredible value in learning what not to do. Again, you need to fix this across all courses - and this goes for all such platforms. Thank you, there is some value in taking a course - we all want more
By Michał O•
Not for the impatient.
3rd and 4th week assignments are quite problematic:
3rd week is heavily dependent on python and libraries versions in user's environment and the course does not point which combination is the one which will be graded correctly. Took me 3 long debugging sessions to finally find the right one.
4th week involves taking had photos to get some gesture recognition. I've spent over an hour with constantly crashing web browser and different cameras to get it right.
Although the skills that can be learned in this course can be really useful, the unnecessary hardships prevent me from recommending it to anyone.
By Jochen R•
it is very exhausting to pass the tests due to hardware and software prblems, though the programming is very easy
By Vitalii K•
A lot of explanation of obvious things. Also, excercises are low quality, with Week 3 and 4 quite hard to pass because of technical issues. Week 3 - need specific versions of the libraries, which are not provided, without which "the model is invalid". Week 4 - quite hard to collect training samples for the model to reach required accuracy, since the app crashes after ~200 examples and wipes them out - you have to start again.
By Musalula S•
The course content is very good but the instructions on how to install Tensorflow 2.0 and Tensorflow.js in python 3 are not clear.
week 4 submission....