Loredana's Projects
In this project, we attempt to predict customer churn of a popular (not real) music service. We perform data analysis and machine learning model building on a large amount of data using Spark.
Web development: World Bank API Data Dashboard
Creation of a Python package to plot a well-formatted and well-labeled line graph for a time series.
Companion code and data for the paper "Measuring the input rank in global supply networks"
Config files for my GitHub profile.
For this project, I chose the Airbnb dataset of the city of Florence. Specifically, I attempted to answer the following questions using the most popular Natural Language Processing techniques applied to review data: 1. How do guests experience their stay in Airbnb in Florence? 2. What are the main topics in guest reviews? 3. How best to predict the topic of a new review?
This project creates a machine learning pipeline to categorize disaster events from a dataset containing real messages. It includes a web app where an emergency worker can input a new message and get classification results in several categories.
The project analyzes the interactions users have with articles on the IBM Watson Studio platform, and make recommendations to them on new articles.