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學生對 Coursera Project Network 提供的 Deploy Models with TensorFlow Serving and Flask 的評價和反饋

112 個評分
26 條評論


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....



Jun 17, 2020

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


Jul 04, 2020

Really simple and to the point course. Totally loved it.


1 - Deploy Models with TensorFlow Serving and Flask 的 25 個評論(共 26 個)

創建者 Grzegorz K

Apr 23, 2020

I give 5 but I couldn't finish all the exercises due to the time limit. I would like 30 minutes more if possible. apart from that top class course. reccoment to anyone who learded some model stuff and want to get a grasp about showing them off

創建者 Ravi P B

Jun 17, 2020

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

創建者 M V

Jul 04, 2020

Really simple and to the point course. Totally loved it.

創建者 Anas K

Jul 09, 2020

Great hands-on tutorial for beginners

創建者 giriraj p

Jul 10, 2020

best way to learn, i love it.

創建者 Irina G

Jul 03, 2020

cool project. Cats and Dogs


Jun 09, 2020

As simple as it should be !

創建者 jaikumar14598

Jun 10, 2020

thanks for the course

創建者 Doss D

Jun 14, 2020

Thank you very much

創建者 Subtain M

Jun 10, 2020

Good explanation

創建者 SASI V T

Jul 10, 2020



Jun 01, 2020


創建者 p s

Jun 24, 2020


創建者 Vajinepalli s s

Jun 16, 2020


創建者 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.

創建者 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


Jun 27, 2020

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

創建者 galimba

May 30, 2020

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

創建者 Guillaume S

Apr 11, 2020

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

創建者 Vladimir K

Mar 28, 2020

Course itself is very good but Rhyme experience is terrible

創建者 Tausik K M

Jun 11, 2020

Awesome One

創建者 Rishabh R

Jul 02, 2020

not as expected

創建者 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.

創建者 Rajtilak I

Jun 21, 2020

Terrible course — do not expect to learn anything about Tensorflow Serving. 90% of the course is about building a rudimentary flask app

創建者 Grygorii K

Mar 27, 2020

Only one video demo with no relation to real-life application. Waste of money and time.