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Trained and deployed PyTorch sentiment analysis model. Also, built a model and create a gateway for accessing it from a website.

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iamRishabh07/project--Deploying-sentiment-analysis-model

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project--Deploying-sentiment-analysis-model


Deploying a Sentiment Analysis Model

Project Overview

In this project, I have constructed a recurrent neural network to determine the sentiment of a movie review using the IMDB data set. I have created this model using Amazon's SageMaker service. Also, I have deployed my model and constructed a simple web app which will interact with the deployed model. The prediction model is implemented in PyTorch and deployed to AWS SageMaker.
To serve it on a web page, I call the SageMaker model from a AWS Lambda service, which can be accessed via API Gateway.

SageMaker Deployment Project

The notebook and Python files provided here, once completed, result in a simple web app which interacts with a deployed recurrent neural network performing sentiment analysis on movie reviews. This project assumes some familiarity with SageMaker, the mini-project, Sentiment Analysis using XGBoost, should provide enough background.

Please see the README in the root directory for instructions on setting up a SageMaker notebook and downloading the project files (as well as the other notebooks).

What is it?

It's a deployed web page which defines sentiment of a movie review.

Below are results for some reviews for "Au service de la France":


Positive review


Negative review

Authors

  • Rishabh Srivastava

License

MIT

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Trained and deployed PyTorch sentiment analysis model. Also, built a model and create a gateway for accessing it from a website.

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