Darren Tsang
Applied Mathematics & Statistics @ UCLA '21 🐻
Darren Tsang
Applied Mathematics & Statistics @ UCLA '21 🐻
About
📍 Fort Funston, San Francisco, CA
Hello Visitor!
I'm Darren, and I recently recieved my BS, Applied Mathematics and BS, Statistics from University of California, Los Angeles (UCLA). Before transferring to UCLA, I earned my Associate of Science in Mathematics and Computer Science at Skyline College.
Growing up in Silicon Valley, I've always been surrounded by the world's newest and greatest technological innovations. Because of the combination of wanting to be part of that greatness and the booming field of big data, my career interests are broadly in data science, machine learning, and software engineering. I'm passionate about using my strong programming skills and mathematical background to solve real problems in order to generate positive business impact.
During my free time, you can probably find me catching up on the NBA and NFL, practicing my Chinese, or on my journey to find the best tacos in San Francisco (btw it's currently Tacos El Patrón if you're wondering).
I'm interested in full-time and internship opportunities that would allow me to integrate my creative and technical skills. If you'd like to discuss such opportunities or learn more, check out my resumé, continue reading below, or contact me at darrentsang-at-ucla.edu.
— Darren
Experience
Data Science, Machine Learning Intern @ Cricket Health
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Tags: Python, NumPy, Pandas, AWS, data analysis
Data Science, Machine Learning Intern @ Cameo
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Tags: Python, NumPy, Pandas, AWS, data analysis
Data Science, Analytics Intern @ Block Renovation
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Tags: Python, NumPy, Pandas, AWS, data analysis
Data Science, Analytics Intern @ Second Genome
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Tags: Python, NumPy, Pandas, AWS, data analysis
Projects
What Makes an NBA All-Star?
Consolidated output from an NBA API into 1 clean, organized dataset containing 3430 NBA player seasons and 29 of their respective stats. Performed exploratory data analysis and data reduction techniques to visualize high-dimensional data. Applied kNN, logistic regression, and random forests to predict whether an NBA season was all-star worthy.
Tags: Python, NumPy, NBA API, data visualization, dimensionality reduction, k-nearest neighbors, logistic regression, random forests
Deep-CNN based Robotic Multi-Class Under-Canopy Weed Control in Precision Farming
Created a multiweed classification system for an agricultural robot. Trained on custom-built dataset containing 9500+ images of 15 different weeds. Co-authored research paper accepted to ICRA (International Conference on Robotics and Automation) 2022.
Tags: Python, Tensorflow, Keras, computer vision, robotics, automation
Age Guesser
Used computer vision to predict your age given a selfie. Trained on dataset of 600k+ celebrity images. Analyzed initial results of model and made further improvements based on findings. Presented work and final results to a non-technical audience of ~50 people.
Tags: Python, computer vision, data analysis
Analysis on Video Growth Rates
Applied bagging and random forests to predict growth rate of YouTube videos. Performed exploratory data analysis on dataset to gain valuable initial insights. Executed feature selection to significantly reduce computation times while maintaining respectable results. Successfully passed all 4 thresholds on Kaggle. Made submssions as Red Team 1.
Tags: R, YouTube analytics, feature selection, decision trees, bagging, random forests
Personal Website ;)
Self-taught HTML/CSS/Javscript to create this website. Serves as a portfolio for past experiences and projects. Deployed using GitHub Pages.
Tags: HTML, CSS, Javascript
Coursework
