Deploy Models with TensorFlow Serving and Flask

Deploy Models with TensorFlow Serving and Flask TensorFlow Serving makes the process of taking a model into production easier and faster. Create a web application with Flask to work as an interface to a served model. 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.