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Learner Reviews & Feedback for Deploy Models with TensorFlow Serving and Flask by Coursera Project Network

4.5
stars
172 ratings
33 reviews

About the Course

In this 2-hour long project-based course, you will learn how to deploy TensorFlow models using TensorFlow Serving and Docker, and you will create a simple web application with Flask which will serve as an interface to get predictions from the served TensorFlow model. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your Internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with (e.g. Python, Jupyter, and Tensorflow) pre-installed. Prerequisites: In order to be successful in this project, you should be familiar with Python, TensorFlow, Flask, and HTML. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

Top reviews

MS
Sep 14, 2020

This course helped me a lot, I was confused and looked up a lot of articles on deploying deep learning models with tensorflow but this one helped by a great margin.

RB
Jun 16, 2020

Nice way to get started with model deployment with web app.

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26 - 33 of 33 Reviews for Deploy Models with TensorFlow Serving and Flask

By M M A

Jul 23, 2020

Ok

By Joerg H

Apr 15, 2020

Fine demonstration of the TensorFlow Serving Tool. I Since I have experience with Flask and Docker it was easy for me to follow. I particularly liked the application of the Bootstrap library, which I didn't use yet. As a potential for improvement I would like to propose more coverage of TensorFlow Service itself (I guess it is also possible build and train new models - but maybe this is beyond the scope of a short project...) By this course I feel inspired to use TensorFlow Serving and learned how to set a defined model in short time.

By José C G M

May 29, 2020

The virtual machine could be properly configured so as not to waste time on problems that arise. Also, I found the Rhyme platform with bugs

By JAVIER A T L

Jun 27, 2020

Time given for the virtual desktop is not enought if you actually type and try everything he does.

By galimba

May 30, 2020

This workshop is very helpful but I would have liked something a bit more advanced.

By Guillaume S

Apr 11, 2020

More oriented toward using flask than on TensorFlow Serving but well done.

By Rishabh R

Jul 2, 2020

not as expected

By Jean M

May 15, 2020

The course is too basic. The course doesn't even train the model. It would be much better to prepare everything from model creation to deploy and serve. The browser-based tool used to code is horrible.