My name is Kyle Huynh, and I am currently an undergraduate student at the University of California, Irvine, studying Data Science! I have a passion for all things data 📈, and I find the entire data lifecycle—from cleaning and visualization to modeling and deployment—fascinating.

Currently, I participate in research focusing on machine learning and deep learning models in the fields of health and environmental sciences. While my primary interest lies in data science, this profile showcases my various passion projects developed over the years!

• Description: JotGenius is an innovative web application that gamifies the note-taking experience, making it more engaging and interactive. By leveraging Google Gemini AI, users can receive scores based on the quality and creativity of their notes. The front end of the application is built using Tailwind CSS and Next.js, ensuring a responsive and visually appealing user interface. The back end utilizes Python and Flask to manage API calls and facilitate seamless interactions with the Gemini API, providing users with real-time feedback on their note-taking performance.

• Outcome: Successfully created a dynamic and user-friendly platform that encourages effective note-taking habits through gamification. The application not only enhances user engagement but also provides valuable insights into their note-taking styles, fostering continuous improvement. This project showcases proficiency in both front-end and back-end development while utilizing AI to elevate the user experience.

• Description: A data science project that analyzes and attempts to predict on the stratascratch sepsis dataset.
• Outcome: Developed a machine learning model achieving 90% accuracy in predicting sepsis, recognized for the best use of sepsis data during the UCI Embark 2023 Datathon

• Description: A data science project that used a classification model to predict whether a house in Dublin would be booked or not using AirBNB housing data.
• Outcome: Implemented a Random Forest classifier model with a 90% accuracy rate on the test data.

I would love to hear from you! Whether you have questions, comments, or just want to connect, feel free to reach out through any of the following methods:

• 📧 Email: You can contact me via email at: [email protected]

• 🔗 LinkedIn: You can connect with me on LinkedIn at: Click Me!