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 tutorial for how build a web application that uses DataRobot to classify movie ratings by audiences. 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/.
-
To deploy, you can use the free Vercel Now.
To follow along the tutorial check out the start_exercise
branch.
To see the finished application check out the complete
branch.
If using the complete
branch, replace the values in movie-rating-classifier/api/_env.js
with your values from your DataRobot installation.
- Run
vercel
to deploy - Run
vercel dev
to run locally (but you need to deploy it once first)
movie-rating-classifier/
- The React app and 2 serverless functions, ready to be deployed to the Vercel now or similar service.resources/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.