This is the final solution of the project 'Sagemaker Deployment' which consists in deploying a Sentiment Analysis model using LSTM Classifier 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:
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.
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/NeeharikaGonuguntla/sentiment-analysis
exit
I created a simple webapp that is can be used to analyse if the given review is positive or negative.
You will see the following:
