I am an experienced researcher with professional experience in conducting high-level statistical analysis. While attaining my degree in Data Visualization, I also completed courses in machine learning and conducted a research project using natural-language processing and machine learning text analysis.
Machine Learning Projects
Patterns of Professional IDentity
Using unsupervised machine learning (K-means clustering) and natural-language processing, I identified seven professional identity themes of 466 math and science teachers. This research and visualization was designed for educators, researchers, and administrators to better understand teacher retention in STEM education.
Supervised Machine Learning
I also have experience with supervised machine learning projects which includes predicting helpful scores from over 350,000 Amazon reviews and identifying planes from over 6700 images.
Amazon Review Predictions
As part of my machine learning class, I had to create algorithms to predict the helpful score Amazon reviews. Using Python, I trained and tested several models using linear regression, logistic regression, Naive Bayes, and Perceptron. I reached accuracy scores at over .90 and precision scores over .65.
Identifying Plane images
Using scikit-image, I created algorithms that identified planes from over 4700 photos. I used Perceptron and Neural Network models to identify plane images with precision and accuracy scores over .95.