This course covers building ML models with TensorFlow and Keras, improving the accuracy of ML models and writing ML models for scaled use.
VC
I feel this course very valuable because it taught how to create an automated service in cloud with very huge data and working with distributed systems in production environment with minimal time.
TW
This needs some updating - looks like the Tensorboard is no longer accessed in the same way as it was when this course was produced. Otherwise great! Good challenges! :/
TB
Great course as an introduction to TF, however, the labs are not as in depth as I'd have liked. Nonetheless, the course is well executed by the presenters.
AJ
Excellent 'Introduction' to TensorFlow 2.0 (HINT: 'Introduction' does not mean 'Easy').Evan Jones is at his best giving rapid intuitive explanations of advanced topics in deep neural networks.
PR
Amazing course! The short length of videos makes it lot easier for students to follow! Google is honestly the best at whatever it does! :)
JZ
Quite a technical course with sophisticated lab sessions, but I got good hands-on experience on building NN models using Keras and TF functional API as well as deploying the model in Vertex AI.
SR
Nice start. Have a look at Andrew NG's course, especially how they do the labs. Might give you some ideas for your next class versions.
SK
A good understanding of bash cmds and a well-digested understanding of the course material is required to perform the labs. Quite challenging.
KW
pretty good. some of the code in the last lab could be better explained. also please debug the cloud shell, as it does not always show the "web preview" button ;) otherwise, good job!
LL
The tools and methods presented were great. The instructors were also fantastic.However the coding exercises were lacking in guidance even though the complete solution is given in the video.
YG
The procedure to connect to the cloud datalab was time consuming to do it every time.Suggestion : More topics in Core Tensorflow could be added. I enjoyed the course!
SJ
Wonderful course and specilization to deep dive into ML. Take your time and work on this course with all your heart to get in to the heart of ML