Convolutional Neural Networks in TensorFlow

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.

A brilliant hands-on course that really gets the student into ML with tensorflow / keras ... Also lots of kudos to our teacher Laurence for a great course.

Could have dived more into the details and inner workings of Convolutional layers but overall awesome course.

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

Please transfer the notebook from CoLab to Coursera.

First, I think the course was great, very instructive. Thanks to Andrew and Laurence for putting this together, is a great source of information to understand more about DL. Some things I think could improve the course. I found the transfer learning lessons a bit unclear and I struggle generalizing this to other cases. Also, I was a bit confused by the flow of the course. The course starts with a multi classifier (or actually, the previous course), then the lessons focus on binary classifiers and it ends again with multi classifiers, because these should be the more complex ones.One last technical thing, only on the last lesson of this course it is mentioned that the classifiers output the probabilities on alphabetical order when using ImageDataGenerators (or at least, that's my impresision). I've wondered since the course introduced the ImageDataGenerators, how the probabilities are assigned on the outputs. I could figure out on the sigmoid that the classifier would look for the first class on the directory and output 1 or 0 based on that, but it would be good to have this mentioned at some point on the video when the ImageDataGen is introduced.Thanks again! Great course

Practice with various data sets, and learn the tools to use for convolutional neural networks with tensor flow

Keep learning! Thank you!

excellent

Thank you.

Hands-on and straight to the point.

good