Good intro course, but google colab assignments need to be improved. And submitting a jupyter notebook was much more easier, why would I want to login to my google account to be a part of this course?
Great course to get started with building Convolutional Neural Networks in Keras for building Image Classifiers. This is probably the best way to get beginners into Deep Learning for Computer Vision.
By Dmitriy S•
The lections were good enough, but the assignments are awful. In the first week, they say we can use TF 2.0, the Google Colab uses TF 2.3, the grading script accept only TF 1.14. I spent a lot of time only to figure out which version syntaxis should be used in order to pass the grader. That was awful.
By Kenny H•
Not going to lie, I'm pretty disappointed after finishing Andrew Ng's course and coming here for the next step. I feel like maybe Andrew raised my standards too high, but this course was extremely not begineer-friendly as an intro course, and I don't think I was able to pick up anything worthwhile.
By Shahar M•
The professional content is very poor - it cover very little and only the very basic meaning is taught . I have expected a much more in depth technical learning and a little more theory. All the course taught is how to write 20-30 lines of code... disappointing.
By Jonas H•
Good course content 5/5 for it. However, the last exercise is prone to errors due to the system. There are many posts in the forum and none of them have a response by the staff. Considering this is paid content I'd expect staff to address the problems.
By Mojgan M•
The code in googlecolab was not organized well and the course content was so basic. I expected more from this course when I started as I took course of ML with Andrew Ng and expected the same level of quality but got disappointed.
By Katerina M•
Amazing lecturers and good structure thus 2* but the content would be 1* because it is far too basic and this certificate is unusable to show anywhere because of that. The tasks one up to 3 hours to accomplish it? 5 min max...
By Lukas S•
Introduction to Keras would have been a more appropriate title. A bit disappointed, that the course just scratched the surface of tf.keras instead of explaining more concepts of the (much bigger) tf library.
By Artem R•
No theory at all. Not much explanation regarding TF classes, functions and their arguments. Just basics of TF. Most of the assignments can be solved with copy/paste from examples.
By Aleksey V•
Just a brief introduction to TensorFlow, very basic and short on practical exercises. I literally copy-pasted texts from one notebook to another. Neither gives it a lot of theory.
By Jonathan P•
Programming exercises are quite sub-standard. Explanations in video lectures are too short and coarse. Andrew Ng's deep learning specialization far superior, stick with that
By Dan G•
The exercises are very repetitive and basically just copies of the notebooks in the course. There is no thinking required for this course. The material is very shallow.
By Laha A•
I would say it is a introduction to Keras rather than Tensorflow. The course not really touch tensorflow, it all about the high level API which is Keras in TF.
By Mohammed E•
the notebooks have a poor explanation of what should be done and unless you delete the last two cells every time you won't be able to submit
By Prantik R•
This course needs to be more beginner friendly....it directly jumps to advanced concepts without clearing the intermediates
By Matthew R•
Really superficial overview of tensorflow and deep learning. Very few concepts were explained in any real depth.
By Suraj R•
Resources shown in the video were not included as web links, so the course couldn't be completed
By Rudrani G•
A little too complex for beginners. Content must be explained from a novice point of view
By John M•
Some reading exercises had missing links and some code used a deprecated function.
This course teach how to use Keras more than using Tensorflow
By Francisco R•
It´s well explained but way too basic and short.
By Xixi W•
这课挺水的， 不如 deep learning specialization多矣。
By Alejandro D•
notebooks need work from the instructors
By Deleted A•
Course was not rigorous enough
By Reinier V•
By Peter C•