AWS SageMaker - Sentiment Analysis Prediction of Text put in an S3 Bucket

This project is just an example of how to use AWS SageMaker to make AI prediction. I used a free model/algorithm package available on AWS Sagemaker ( "knime-sentiment-model-package" ) to identify the sentiment (positive/negative) of a given text in English. The project contains following folders:

-ui: NodeJS config file + AWS JS SDK + S3 Functions

-lambda: Python lambda file

-examples: text examples

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

• Buy a (FREE) AWS SageMaker model+algorithm and setup the endpoint
• Create the S3 Bucket in AWS
• Create a Lambda to be triggered on the S3 Bucket Event (put)
• Setup CORS permission on Bucket
• Setup Amazon Cognito for Browser Identity management

Installing

cd ui

npm install

node server.js

Running the App

Execute Installing instructions and then go to http://localhost:8080/

Authors

Stefano Patitucci