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Multi-Document Summarization Engine
An extractive document summarization engine.
I am a computational linguist formally trained through the M.Sc. program at the University of Washington. My passion for language began with my undergraduate studies in linguistics and evolved into a curiosity about how we can get computers to carry out meaningful tasks on data as complex as human language. Through my studies and personal projects I now have experience building pipelines with many of the common Python machine learning libraries as well as writing NLP algorithms from scratch. I love a challenge and am always looking for new opportunities to learn and grow. I've even dipped my toes into a bit of web development and data visualization out of personal interest!
An extractive document summarization engine.
An investigation of how labeled training data can be bootstrapped for a named entity recognition task in the absence of professionally annotated data.
My solution to the Detroit Blight Ticket Compliance competition on Kaggle.
A neural text classification project.
Plotting the relationship between COVID-19 cases and shelter occupancy in Toronto, ON.
A website I built for a professor at York University.
An implementation of an interactive bar chart with error bars as described in Ferreira et.al (2014).