A continually expanding collection of personal projects interweaving concepts of programming, machine learning, and domain knowledge within the clinical and cognitive sciences.
My most recent projects include employing knowledge of HTML and CSS to create the current website and exploring textual expressions of clinical symptomology with natural langauge processing and ensemble learning algorithms.
Text-based analysis determined general semantic patterns, sentiment and LDA topics common to expressions of either anxiety or depression through the use of 10,000 anxiety and depression focused tweets pulled via the Twitter API. Ensemble learning algorithms best classified text as either anxiety or depression-focused.
Skills: Python, NLP, Sentiment Analysis, Topic Modeling, Unsupervised & Supervised ML
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Examination of suicide rates per country as scraped from Wikipedia. Associations with mental illness prevalence, unemployement rates, GDP expenditure and gender ratios visualized prior to ML classification of countries' overall suicide rate as compared to the global average. See related Tableau viz here
Skills: Python, Webscraping, Exploratory Data Analysis, Supervised ML, Tableau
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Exploration and prediction of what professional and personal experiences impact tech employees' expectations of mental health conversations in the workplace.
Skills: R, Data Cleaning, Feature Selection, Supervised ML
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