Machine learning internship
I had the privilege of participating in the undergraduate research experience, where I learned how to train a machine learning model. During this program, I gained insights into the mechanisms of training AI systems, particularly through hands-on experiments with convolutional neural networks, image classifiers, and adversarial patches. I tackled challenging tasks that involved training models for image classification and deception using diverse datasets, fine-tuning loss functions, and leveraging the computational power of the NVIDIA Jetson Nano. A highlight of my work was the development of a robust shaped patch, able to effectively fool the YOLOv2 model!
