About Me
Curious. Problem-solver. Empathetic.
I am a strong believer of the need of
Data Science and Machine Learning in today's industries. Data Science
is known to be a buzz
terms, but undeniably will be part of our future. My interest mainly lie in the intersection between Data Science and Data Engineering,
such as productionizing model code, creating data pipelines, and developing real-time analytics dashboard. I am currently pursuing a
M.S. in Data Science degree at
Columbia University to solidify my foundation in Machine Learning and improving my Engineering/Coding skills through projects and internships.
When I'm not solving data science problems, I love to create
websites, webapps, and interactive data visualizations for organizations I believe in (and sometimes
just for fun!).
I am currently looking for an internship for Fall 2019 and a full-time job starting January 2020, so
contact me for any kind of work opportunity. If you just
want to connect and talk about tech, send me a message too!
Data Science Projects
MovieLens: Predicting Ratings with Spark and Hadoop
Analysis of MovieLens using Big Data tools (ongoing).
DL + Cancer: Classifying cancerous cell images
Using Neural Networks and Keras (RNN, CNN) to classify cancerous images.
r/science: Troll detection
Using NLP techniques to classify Reddit trolls from comment content.
NYC 311: How well does the NYPD respond to 311 calls?
Visualizing and discovering patterns of NYPD response to 311 calls using ggplot and D3.js.
Last.fm: Recommending Top-K Artists
Using ALS and FFM models to recommend artists to users using implicit historical data.
Titanic: Who will survive?
Predicting Titanic survivors using sklearn. A first try in Kaggle Competitions!
Web and Software Projects
(Hover to view!)
