Chevron Left
返回到 Create Docker Container with Flask Seaborn Regression Plot App

學生對 Coursera Project Network 提供的 Create Docker Container with Flask Seaborn Regression Plot App 的評價和反饋

45 個評分
7 條評論


Often a software application developed on one platform will not run on another because of software environment differences. Sometimes it can happen when an operating system is updated, for example. Suddenly an application starts to fail. Containers solve that problem by creating a controlled environment in which to run the application, separate from the host machine’s environment. The container contains a specific version of each software package that is known to work with an application at a given point in time. Docker is an application that allows the developer to generate containers to easily build and share applications. In this course, you will create a Docker container in which you will implement a web application using flask in a Linux environment. The application will return a regression plot of data housed in a CSV file on the server. Note: 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....

1 - Create Docker Container with Flask Seaborn Regression Plot App 的 7 個評論(共 7 個)

創建者 Mark P


Content great, but Rhyme online virtual platform did not work for me at all. Luckily I had Docker, Flask and Visual Studio installed on my own computer anyway, so could follow along with the video.

創建者 Nathan S


Brings together in one place what you need to know for using Flask to serve images created with matplotlib and seaborn. It's easy to fall along and learn the important details for running this application in Docker.

創建者 Marcin S


I'm rather disappointed with this course. I subtract one star because the app was too easy and didn't show much functionality. At the same time, there was not enough explanation about the visualization part (I did not work with Seaborn previously) so for me, it was just typing presented code. While most parts of this project had not enough explanation I see no point in having an entire video about creating the requirements.txt file, especially because it was done with mistakes and instead should be summarized with one command `pip freeze > requirements.txt`. Finally, the Rhyme platform was not working, but it would be a problem if I could download the data used for this application. I couldn't and I didn't have such problems with other guided projects.

創建者 Tatiana M


great course

創建者 Kamlesh C



創建者 Ijeoma O


Good project

創建者 Igor K


I had no connection with rhyme during the lesson. doing everything on the local computer.