Please note: The code in these repos is sourced from the DataRobot user community and is not owned or maintained by DataRobot, Inc. You may need to make edits or updates for this code to function properly in your environment.
A project to accompany a workshop on how to build a web application that uses DataRobot to classify movie reviews. Demo: https://movie-rating-app.now.sh/
The app lets you rate the movie and uses ML to clasify your rating in either positive or negative - Rotten Tomatoes style.
It uses DataRobot to create the ML model, deploy it, and expose it as a prediction API, and the movie database taken from from RapidApi.
The movies you can rate are taken from IMDB's top 250 movies of all time.
- You will need a DataRobot account and access to deployments. You can apply for a DataRobot trial account using this link: https://www.datarobot.com/lp/trial/.
- Node.JS
- Pusher account for broadcasting predictions in realtime over WebSocket to other workshop participants(optional)
To follow along the tutorial check out the start_exercise branch.
To see the finished application check out the main branch.
If using the main branch, create a file called .env with your DataRobot values. See sample.env for the variables you need.
server.js- Express Server that makes predictions to DataRobotapp/- React app that serves as our frontendresources/IMDB_Dataset.csv- The training dataset - taken taken from Kaggle and originated in the the 2011 ACL paper - Learning Word Vectors for Sentiment Analysis.
If you'd like to report an issue or bug, suggest improvements, or contribute code to this project, please refer to CONTRIBUTING.md.
This project has adopted the Contributor Covenant for its Code of Conduct. See CODE_OF_CONDUCT.md to read it in full.
Licensed under the Apache License 2.0. See LICENSE to read it in full.