Michael Wirtz's repositories
esg_materiality_analysis
This project is currently in motion. It seeks to run fundamental analysis in conjunction with NLP on small-cap companies to deliver an optimally resilient list of companies to buy long.
movie_profitability_metrics
This project uses simple data analysis techniques to gain insights into the metrics that correlate to movie profitability. This analysis is done in order to advise a new studio on how to make its business optimally profitable.
newsworthy_events
This project leverages NLP to classify tweets into events and non-events. The project recommends usage by news outlets to quickly filter for possible story leads
edf_donation_analysis
This project leverages NLP to lower the advertising and promotions budget of the Environmental Defense Fund (EDF) by pinpointing the time of year and areas of the country that are most likely to donate in the highest numbers
algorithmic-trading-python
The repository for freeCodeCamp's YouTube course, Algorithmic Trading in Python
twitter_classification
This project aims to classify tweets into events and non-events. The project recommends usage by news outlets to quickly filter for possible story leads.
startup_success_classifier
This project identifies companies that will be considered successful based on information sourced from crunchbase. The results are recommended for use by potential VC firms as a filter for potential investments
kings_county_housing
The purpose of this project is to create a model that accurately predicts the prices of houses in Kings County, Washington.
movie_content_analysis
This project finds the most profitable elements in movies. These profitable elements are then formatted as recommendations for a new movie studio.