Notes and reference material to support an instructional unit about database-backed web applications.
Step-by-step "Twitoff App" solution walkthroughs:
- Twitoff for DS 15
- Twitoff for DS PT5
- Twitoff for DS 14
- Twitoff for DS 13
- Twitoff for DS PT4
- Twitoff for DS 12
- Twitoff for DS PT3
- Twitoff for DS 11
The "Twitoff App" data flows are like:
- User provides example tweet text and selects two Twitter users to compare which is more likely to say the example tweet text.
- App requests user and tweet information from the Twitter API, as necessary, to gather data about each user, and stores it in the database.
- For each tweet, app makes request to Basilica API to get corresponding natural language processing embeddings, and stores them in the database.
- App uses the tweet embeddings from both users to train a binary classifier model.
- App makes a request to Basilica API for the natural language processing embeddings for the example tweet text, and passes those to the model as an input value in order to make predictions.
- App displays prediction results to the user.