https://github.com/adeboyeml/sentiment-analysis-udacity-project
This end-to-end project is aimed towards creating a deep learning model using RNN that will be used to determine the sentiment of a movie review (either positive or negative), thereafter the model will be deployed to a simple web app, where a user can write his / her review and the deployed model will be able to determine whether such review is a positive or negative one.
https://github.com/adeboyeml/sentiment-analysis-udacity-project
Last synced: about 1 year ago
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This end-to-end project is aimed towards creating a deep learning model using RNN that will be used to determine the sentiment of a movie review (either positive or negative), thereafter the model will be deployed to a simple web app, where a user can write his / her review and the deployed model will be able to determine whether such review is a positive or negative one.
- Host: GitHub
- URL: https://github.com/adeboyeml/sentiment-analysis-udacity-project
- Owner: AdeboyeML
- Created: 2019-11-10T12:18:35.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2019-11-10T15:13:23.000Z (over 6 years ago)
- Last Synced: 2025-05-20T19:11:38.658Z (about 1 year ago)
- Language: Jupyter Notebook
- Homepage: https://github.com/AdeboyeML/Sentiment-analysis-Udacity-project
- Size: 71.3 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# 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](https://github.com/udacity/sagemaker-deployment/tree/master/README.md) in the root directory for instructions on setting up a SageMaker notebook and downloading the project files (as well as the other notebooks).