Kyle Bradford

I have a strong foundation in machine learning and artificial intelligence, with experience in applying tools like Python, data visualization, and computer vision. My goal is to leverage these skills to solve real-world challenges and contribute to innovative projects in data science or full-stack development.

CSC 495: Accelerating Neural Networks 

Collaborated with a team to design and implement experiments comparing transfer learning and traditional model training approaches.

• Evaluated the performance of multiple neural network architectures in terms of speed, accuracy, and resource utilization.
• Conducted in-depth analysis of training times and model convergence rates across diverse datasets.
• Provided recommendations for optimizing model performance based on transfer learning advantages in real-world scenarios.
• Presented project findings to faculty and peers, highlighting strategies for accelerating neural network computations.

CSC 422: Automated Learning and Data Analysis
Developed a machine learning model to predict new songs for a playlist based on the audio signature of existing tracks. 

• Utilized machine learning algorithms to predict new songs based on similarities in audio signatures, including tempo, energy, and key.
• Conducted data preprocessing and feature engineering to improve the accuracy of song recommendations.
• Evaluated the model using real-world playlists and metrics such as accuracy and precision.