Deploy Machine Learning Model into AWS Cloud Servers

4.3
29 個評分
提供方
Coursera Project Network
在此指導項目中,您將:

Build a machine learning-based spam detector API

Deploy the machine learning application into AWS virtual servers.

Clock2 hours
Intermediate中級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

By the end of this project, you will learn how to build a spam detector using machine learning & launch it as a serverless API using AWS Elastic Beanstalk technology. You will be using the Flask python framework to create the API, basic machine learning methods to build the spam detector & AWS desktop management console to deploy the spam detector into the AWS cloud servers. Additionally, you will learn more about how to switch between different versions of your web application & also, monitoring your AWS servers using Elastic Beanstalk Desktop Management Console. Note: To avoid distraction for set up during the course, we would recommend that you create an Amazon AWS account beforehand. Amazon AWS provides a free tier option for 1 year & the course materials will utilize services that fall under the free tier option.

您要培養的技能

  • aws
  • EC2
  • Aws Elastic Beanstalk
  • Machine Learning
  • Python Programming

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  1. Create a Flask application

  2. Create a RESTful API - GET/POST Method

  3. Build a spam detector ML model

  4. Build a spam detector API

  5. Launch an AWS EC2 instance(Virtual Server) using AWS Elastic Beanstalk.

  6. Deploy your ML model(API) into AWS virtual servers.

  7. Perform additional AWS Elastic Beanstalk actions: Application versioning, Server logs, Server performance monitoring & Terminate the server.

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

常見問題

常見問題

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