About Me
Hi! My name is Yuting Gong.
I was born and raised in Shanghai, China, and now living and stuyding in New York.
I got my bachelor degree in Finance and minor in Mathematics from New York University Shanghai, and I am currently pursuing a Master's in Applied Analytics at Columbia University, graduating December 2019
I had over one year of full-time work experience in business intelligence before my master's degree. This summer, I interned as an analytics consultant in data science at an analytics consulting firm, working on Natural Language Processing and predictive modeling.
I would love to work in data science & analytics field after graduation.
Languages: Python, R, SQL
Interests: Fitness (hot yoga is my current favourite), reading
Predictive Modeling Projects
Airbnb Price Prediction
[R]
This is my work on solving “How much for your Airbnb?”, an in-class Kaggle competition. I conducted exploratary analysis and built a random forest model to predict house prices with 53 RMSE.
Movie Revenue Prediction Analysis
[R]
The goal of this project is to find out the important factors that would influence a movie’s revenue, and build a predictive model to forecast a movie’s revenue. The best model (xgboost with text mining) reached a rmsle of 2.1.
NLP Projects
Sentiment Analysis of Amazon Product Reviews
[Python]
I conducted sentiment analysis on Amazon product reviews of toothpates. In the supervised sentiment analysis, I built a XGBoost with Word2Vec model reached 93% accuracy and 92% weighted F1 score.
An Analysis of Song Lyrics
[Python]
What topics to write about for different music genres? What words to use? How long should the song lyrics be? Not sure where to begin? The report is an exploratary data analysis of song lyrics aiming at understanding the characteristics of lyrics for different music genres.Techniques used in this project are: LDA Topic Modeling, Wordcloud and tokenization.
Interactive Web Application Projects
U.S. Alternative Fuel Stations - Interactive Data Web Application
[R Shiny]
This Alternative Fuel Calculator Interacrtive Web Application helps eco-friendly drivers find nearby alternative fuel stations and calculate the estimated price of alternative fuels they need to get to their destinations. This app also contains an analytics report that shows some preliminary data analysis results to help people learn more about how alternative fuel is adapted in the U.S.
Automatic Topic Modeling Web Application
[Python, Flask]
Topic Modeling is a type of machine learning model that helps to extract 'topics' from a collection of documents. The goal of this flask project is to develop a user interface that embeds the LDA Topic Modeling algorithms, and make it easy for even non-technical people to extract topics from any texts data.