Projects

In my free time, I am learning new skills by working on projects that highlight my interests. Here are a few that I am most proud of.

Machine learning

• Reinforcement learning for Snake
  • Training agents to play Snake using techniques from reinforcement learning. Tabular Q-learning and Value Function Approximation are implemented (using a simple Neural Network) in Python.
• Predicting Response Times of the San Francisco Fire Department
  • Predicting response times of the San Francisco Fire Department Using Apache Spark and MLlib.
  • The process was published in this research paper.
• Predicting Reddit Comment Upvotes
  • Predicting how many upvotes a comment will get, given the comment text, user history, subreddit and thread details. Uses Python and scikit-learn.
  • The associated blog post highlights the workflow and provides a tutorial for those who are new to machine learning, Python, or scikit-learn.

Data visualization

• Spotify Wrapped: Data Visualization and Machine Learning on Your Top Songs
  • Using Spotify Wrapped playlists to tell a story with visualizations and analysis. Created classification models to predict which user would prefer a given song as well.
  • The github repository contains the Python code used to create the plots with popular tools like matplotlib and plotly and to create and compare machine learning models with scikit-learn.
• The Simpsons Meets Data Visualization
  • Analyzing the episode scripts to tell a story with visualizations and analysis.
  • The github repository contains the Python code used to create the plots with popular tools like matplotlib, plotly, seaborn, and altair.
• California Apartment Listings
  • A shiny dashboard that displays apartment listings in California.
  • The github repository contains the R code used to create the application.