FDA Noncompliance Predictor
Deployed logistic regression model that predicts FDA food safety noncompliance (0.98 testing precision).
Python: SKLearn, NLTK, Statsmodel, Pandas, Numpy, Matplotlib, Seaborn | Streamlit
I am passionate about solving business problems at-scale with automative AI technologies and committed to
developing both internally and externally trustworthy AI to protect citizens (especially underprivileged groups).
Please refer to my "Tailored Profiles" section at the top for an audience-specific portfolio.
Deployed logistic regression model that predicts FDA food safety noncompliance (0.98 testing precision).
Python: SKLearn, NLTK, Statsmodel, Pandas, Numpy, Matplotlib, Seaborn | Streamlit
Interactive Streamlit app that deploys a deepfake image detector (0.99 validation precision).
Python: SKLearn, Pandas, Matplotlib | Streamlit | Pickle
Full-stack, interactive web app that utilizes machine learning to identify poisonous mushrooms (0.99 validation accuracy).
Python: SKLearn, Pandas, Matplotlib, Flask | HTML/CSS/JSS, Bootstrap, Plotly | GSlides
Full-stack, interactive web dashboard that dynamically displays user-selected data on video game market data.
Python: Pandas, Beautiful Soup, Requests, Pymongo, Flask | MongoDB | HTML/CSS/JSS, Bootstrap, Plotly, Leaflet.js | GSlides
Machine learning project that differentiates between two subreddits: AskReddit and AskScience (0.82 F1 score).
Python: SKLearn, Matplotlib, Pandas, Numpy | Pushshift.io
Server-less web-app built via AWS that allows users to book unicorns for their magical traveling needs.
AWS: S3, Lambda, Cognito, Gateway, and DynamoDB
Front-end dashboard that interactively displays the bacteria biodiversity in belly button samples.
HTML | CSS | JavaScript: Plotly
Back-end ETL process to that extracts, transforms, and loads data to SQL database. Focused on scalability, speed of development, and usability.
Python: Pandas, SQLAlchemy | PostgreSQL