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4- Deploying a Sentiment Analysis Model Project is a part of Udacity Deep Learning Nanodegree

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4-Deploying-a-Sentiment-Analysis-Model

4- Deploying a Sentiment Analysis Model Project is a part of Udacity Deep Learning Nanodegree

Final solution of the project 'Sagemaker Deployment' which consists in deploying a Sentiment Analysis model using RNN in the Amazon AWS SageMaker tool. The notebook and Python files provided here result in a simple web app which interacts with a deployed recurrent neural network performing sentiment analysis on movie reviews.

In the final architecture AWS API Gateway and AWS Lambda functions is used as well. The application architecture diagram is:

Web app Diagram

You can find the original code without solutions in the original Udacity SageMaker Deployment repository.

This project assumes some familiarity with SageMaker, the IMDB Sentiment Analysis using XGBoost mini-project (which can be found in the original repository) should provide enough background.

Setup instructions

Please see the original README in the root directory for instructions on setting up a SageMaker notebook and downloading the project files (as well as the other notebooks). For the solutions only clone this repository:

cd SageMaker
git clone https://github.com/hjlopes/sagemaker-sentiment-analysis
exit

Web app final result

The final project will be executed in a simple html page which can be deployed anywhere.

You will see the following:

Web app example

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