This is my project folder for the metis bootcamp (Spring 2018). You will find 5 main projects in this folder:

EDA on MTA Turnstile data of NY to find optimal stations to target donors and attendees for a tech event.
Tools: Pandas, Google geocode API
Data Source: NY MTA

Medium Blogpost
Using Linear Regression to predict the Box Office on opening weekend.
Tools: Web scraping with BeautifulSoup & Selenium, various APIs, Scikit Learn, Statsmodels.
Data Source: Youtube, Google Trends, OMDB (IMDB, Metacritic, Rotten Tomatoes), BoxOfficeMojo, Bureau of Labor Statistics

Utilized a gradient boosted decision tree to predict the occurrence of a West Nile virus in Chicago using climate & geolocation data. Hosted a Flask app for model prediction and an interactive visualization using Tableau.
Tools: PostgreSQL, CatBoost, Tableau, Flask, D3.js, AWS

Medium Blogpost
Extracted customers' opinions across different aspects of a restaurant (i.e. food, service, ambience, and price) to derive actionable insights for restaurant owners and to allow Yelp users to compare similar restaurants.
Tools: scikit-learn, MongoDB, word2vec, spaCy, AWS, plotly

Tableau Dashboard
Forecasted hourly demand for Uber across 140 locations in NYC using statistical models and RNN approaches to recommend better locations for drivers and reduce surge pricing events.
Tools: Keras (GRU, LSTM), Tableau, Facebook Prophet