I am a Computer Science major and a Legal Studies Minor with a concentration in Artificial Intelligence as well as a Certificate in Managerial Analytics from Kellogg Business School. I am passionate about implementing AI technologies into legal and financial industries. I enjoy learning about different Machine Learning techniques and utilizing data to tell stories through data visualizations. I hope to continuously learn new skills and hopefully contribute to exciting industry projects in law firms.
💻 Python, SQL, Ruby, React
🧰 AWS, Google Cloud Console, Virtual Studio Code, Kaggle
📦 Tensorflow, Keras, PyTorch, Scikit, Numpy, Pandas
Summary: Created a Neural Network Model that performed Sentiment Analysis on a CSV file of Responses; Model categorized responses as Accepted, Rejected, or Neutral
Summary: Created a Linear Regression Model that predicted a country's confidence in their government based on data from the World Happiness Report
Summary: Utilized AWS Rekognition to create a program that compares an input image to a dataset of Avengers, performs a facial analysis of both images, and outputs the Avenger that the input image is most similar to
Summary: Developed a predictive Random Forest Ensemble model for sex and ADHD diagnosis using functional brain imaging, socio-demographic, emotional, and parenting data
Summary: Cleaned data containing Biographies and classified as Fake or Real using a pretrained BERT Model that was then finetuned and compared to a baseline Logistic Regression model
