One challenge i have faced is with deploying the trained models. I find very little coverage on that across courses. It's one thing to save a model.h5 or model.pb. It would be nice if you can add a small piece on deployment of these models using TF Serving or something similar. There is some distance between just getting these files outputted and deploying. TF documentation is confusing about some of these things. Would be nice if you can include a module on that.

Exellent tutorial for using Tensorflow and convolutional networks. Useful usage examples, interesting and challenging exercises. A few minor mistakes prevent five star grading. But please note that mistakes happen and we have to live with this :-). Nice work, looking forward for the next course of the specialization.

This course explores the topics of the first course for image classification with neural networks. All the tests are multiple choice questions. There are some code examples to work with as well as extra exercises but it would have been good to have a programming test as well.

This is another great course in the specialization. I wish only there were graded exercises like the previous course that we can submit and get a grade for. I understand maybe this is due to the long time of training and that is not possible to do.

Maybe a bit repetitive, when you just finished Course 1. We see a lot of lines of codes explained again from course 1 and I think that could be avoided.

However, the new concepts are nicely introduced and very interesting to implement!

It was good, but similar to other learners I feel a little light in content. Though in tandem with the deep learning specialization gives a good view on convolutional neural networks as well as its implementation in tensorflow.

Loved the course. I would have liked a module on saving your own models and then loading them later. The Inception one is nice, but it comes with some "niceties" that I don't think you have with loading a home grown model.

It's an great course with simple explanations about the Deep Learning topic. It's a perfect fit for beginners or those who want to have a practical review before starting using Tensorflow 2.0 with keras implemetations.

The course is really nice. But would be better if the convolutional layers were a bit more detailed. It was a bit difficult for me to understand all the parameters e.g: input/output filter size.

The course was fine sometimes I feel too easy. I would like to see more of the available options for the layers, such as padding, stride. filter size, mean average, batch normalization, etc...

I think this was a good course but the standard of exercises and quizzes was too easy. More conceptual questions especially in quizzes would help in understanding the topic better

the last exercise needed a big upload, made it imposible (for me) to do. This was a problem not related to the subject, should use data downloadable directly from internet.

Very good course that teaches you basics of convolutions, augmentation, transfer learning. Thank you to Mr. Moroney and the Coursera team for making it available.

I think most much of the course conent was same as the first course, this course could have been a little more advanced. But overall a great place to start.

The course content was quite good and overall understandable but the exercises and quizzes were quite easy, they could have been more challenging

very practical courses on implementation of CNN in tensorflow. Suggest student also take the deeplearning series with this series.

Instructors are really good, but in my opinion, this course should contain Object Detection and Object Segmentation topis.

Great introductory course to learn the application of TensorFlow with Keras in the field of Convolutional Neural Network.

Es una gran continuación al curso anterior. No se puede hacer sin haber hecho previamente el otro curso

Course is good to start but it should include other aspects of neural network than image processing.

Very interesting course. I've learned a lot. I would like to have a little more advanced topics

It's a wonderful course! Pity that the data for the fourth exercise are not available anymore.

Great insight for the practical aspect of TensorFlow, add value on top of Andrew's DL courses.

I hope it will be upgraded with graded weekly test (case study and building some models).

Good content, but lacks exercises that forces us to code ourselves to solve the problemas