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COLIN LEVINE
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Trained on a dataset comprising 13,000 lines of classical music, the model utilizes Long Short-Term Memory neural network architecture to capture intricate patterns and structures present in musical compositions. Additionally, the model seamlessly converts the generated music from text to MIDI format and synthesizes it into a WAV file, emulating the sound of a grand piano.
This full-stack development project is designed to facilitate secure video communication through peer-to-peer connections. Implementing a WebRTC signaling server hosted on Google Cloud ensures seamless peer-to-peer video connections. It also supports as many users in each room as the computer can handle.
This study aid platform was developed to improve study skills and exam preparation through active recall, leveraging the power of GPT 3.5 Turbo from OpenAI. Inspired by the scientific effectiveness of active recall in learning, the platform assists users in comprehending complex topics and provides guidance to reinforce understanding.
This hackathon was an opportunity for me to teach a team that was entirely new to web development. Together, we designed, built, and deployed a full-stack web application in just 24 hours. The project provides AI-generated course descriptions from GPT 3.5 Turbo, grade distribution graphs, and professor reviews for each computer science class, all within a single platform. The app was deployed on Google Cloud, ensuring accessibility for all students.
Hi, my name is Colin Levine, and I'm a sophomore engineering student at Texas A&M University planning to complete my Bachelor's Degree in Computer Science.
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