Deploy Models with TensorFlow Serving and Flask
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.
由 MV 提供2020年7月3日
Really simple and to the point course. Totally loved it.
由 JL 提供2020年6月26日
Time given for the virtual desktop is not enought if you actually type and try everything he does.
由 MB 提供2020年12月10日
Excellent! I will rate this as the best rhyme project that I have done so far. The instructor does an excellent job in explaining all the parts.
由 GS 提供2020年4月10日
More oriented toward using flask than on TensorFlow Serving but well done.