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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

4.5
138 個評分
30 條評論

課程概述

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....

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RB

Jun 17, 2020

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

MV

Jul 04, 2020

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

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26 - Deploy Models with TensorFlow Serving and Flask 的 30 個評論(共 30 個)

創建者 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.

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 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.