[email protected] | (970) 310-9988 | Denver, CO |https://github.com/jesseptao
I am an electrical engineer turned data scientist that strives to improve the communities around me through my passion in programming and math. Using a variety of web development and data analysis tools has allowed me to collect and store geographical data, build applications and generate automated pipelines that have actionable insights. By combining my various technical skills, I am able to create innovative tools with a positive impact that seamlessly translate to the real world.
Packages: Scikit-learn, Pandas, Numpy, NLTK, BeautifulSoup, Tensorflow, OpenCV
Data Visualization: Seaborn, Matplotlib, Folium
Modeling: Statistical Modeling, Regression Models, Classification Models, Time Series Forecasting
Spotify Recommender, General Assembly
Created a recommender model for Spotify that recommends new songs from new and less known artists based on what a user previously listened to. Compared songs using their audio files by transforming the audio file into MFCCs and taking the cosine similarity as well as calculating pairwise distances between songs using Spotify API's audio features call. Designed a web application so users can get recommendations as well as give feedback on the recommendations.
COVID-19 Vaccine Distribution, General Assembly
Worked with 3 other students in my cohort to predict the number of COVID-19 cases in each county in California using LSTM, ARIMA, and SARIMA models to improve vaccine distribution by allocating more vaccines to counties where outbreaks are predicted to happen. Built a web application with an interactive map and table to display the results of our findings.
Subreddit Analysis, General Assembly
Used various classification models and NLP in order to determine if a post came from either the Pokémon Go subreddit or The Silph Road subreddit to see if The Silph Road subreddit contains language that is more commonly used by veteran players of Pokémon players.
Ames, Iowa Real Estate Analysis, General Assembly
Predicted housing prices in Ames, Iowa by exploring a dataset with over 80 housing features. Engineered features such as one-hot encoding and interaction terms to build a linear regression model to accurately predict home prices and help prospective home buyers determine if they are paying a fair price for their house. Winner of Kaggle competition in my cohort with lowest root mean squared error for predicted home values.
TaoPokéMap – Web Development Lead August 2018-Present
Tao Innovation Labs Fort Collins, CO
done using the native Pokémon Go app
Pulse – Firmware Engineering Lead August 2017-May 2018
CU Engineering Senior Design Project Boulder, CO
device to help visually impaired individuals detect eye-level objects
on a Raspberry Pi
University of Colorado Boulder (CU) Boulder, CO
Bachelor of Science, Electrical and Computer Engineering, GPA: 3.2/4.0 August 2014- May 2018
Data Science Immersive Remote November 2020-February 2021
models, web scraping, APIs, NLP, advanced supervised learning, unsupervised learning, SQL,
time series analysis, data engineering, deep learning, and Bayesian statistics.
learning techniques on these data sets to create projects that were presented to non-technical
and technical audiences.