Deploy a machine learning model with AWS Elastic Beanstalk
A complete guide to serve a sentiment analysis model using AWS Elastic Beanstalk
Published in
10 min readOct 3, 2019
We present a comprehensive procedure to serve a FastText sentiment analysis model using AWS Elastic Beanstalk. We provide all you need to get your own on-demand sentiment analysis service in 5 languages.
A lot of resources are available on the web to code and train a machine learning model. However, when it comes to deploying and putting it in production, tutorials and procedures become scarce. We try to fill this gap by providing information to:
- Learn how to deploy a basic flask app on AWS Elastic Beanstalk
- Learn how to implement your machine learning model
- Learn how to test your sentiment analysis model
- Understand the difference between Elastic Beanstalk and Amazon SageMaker to serve a machine learning model (pricing/pros & cons).
- Get your own on-demand sentiment analysis service.
Prerequisites
Below is the list of what you will need to go through this tutorial:
- An AWS account. Create an AWS account; it’s free.
- Basic knowledge of Python