stevenhastings / TweetyPy

Full-Stack application that allows client to use a predictive model to determine which user is more likely to have tweeted a given text. This project covers everything from API's to Predictive Modeling, SQLAlchemy database storage, Flask, along with other full-stack components. In the end it is deployed for online usage using Heroku.

TweetyPy

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• This application allows a client to use a predictive model to determine which user is more likely to have tweeted a given text
• Developed framework using Flask Python that queries the Twitter API for tweets from various users
• Implemented word2vect using a SpaCy NLP model to create embeddings from the tweet text
• Stored embedded tweet data in a SQLAlchemy Database
• Fit Scikit-Learn Logistic Regression model to tweet data to make predictions, serializing the results for online use

app.py Project Main File

models.py Database

twitter.py Natural Language Processing

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