A repository of projects submitted during my time in General Assembly's Data Science Immersive course.
- Project 1: How much does the economic background of students in US states affect their ACT/SAT scores and participation rates? (EDA)
- Project 2: In the process of maximizing profits, a company that specializes in flipping houses wishes to identify which are good/bad properties, and which areas they should focus on renovating that will improve the housing prices more efficiently (Regression)
- Project 3: using machine learning models to identify whether the prospective customers wishes to know about homebrewing or winemaking by scraping reddit posts (Classification)
- Project 4: train a model which can predict the prevalence of the West Nile virus amongst mosquitoes within the Chicago city area, and to run a cost-benefit analysis to determine the most effective way to apply pesticides
- Capstone: creating a question and answer generator (both answer-aware and answer-agnostic) based on text given to the model.