Create Docker Container with Flask Seaborn Regression Plot App

4.4
estrellas
42 calificaciones
ofrecido por
Coursera Project Network
2311 ya inscrito
En este Proyecto guiado, tú:

Use flask to create a web application that returns a plot.

Build a requirements document with packages needed for the application.

Build the application using a Dockerfile and test it.

Clock1 hour
AdvancedAvanzado
CloudNo se necesita descarga
VideoVideo de pantalla dividida
Comment DotsInglés (English)
LaptopSolo escritorio

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.

Habilidades que desarrollarás

LinuxData ScienceDockerPython ProgrammingFlask

Aprende paso a paso

En un video que se reproduce en una pantalla dividida con tu área de trabajo, tu instructor te guiará en cada paso:

  1. Install a Linux image into a docker container.

  2. Use the Pandas package with Seaborn to create a regression plot.

  3. Use flask to create a web application that returns a plot.

  4. Build a requirements document with packages needed for the application.

  5. Build the application in a container using a Dockerfile and test it.

Cómo funcionan los proyectos guiados

Tu espacio de trabajo es un escritorio virtual directamente en tu navegador, no requiere descarga.

En un video de pantalla dividida, tu instructor te guía paso a paso

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