This course was taken at the University of the Pacific during the Fall semester of 2022. COMP 191 is an independent study course in which any student can enroll into, but what they pursue in their study is unique. The student works alongside an appointed professor that has expertise in the topic. The student and professor work together to create a course-plan proposal which is then presented to the Dean of the department.
I have taken a Machine Learning course here at university, and enjoyed it quite a lot. So much so I became a teaching assistant for the class However, the class was heavily theory based. Don’t get me wrong, theory is incredibly important, but I live by the idea that we truly learn when doing. My reason for taking part in independent study is to get hands-on experience with ML frameworks.
Though the course title emphasizes independent study, this course was taken alongside two of my peers, Ethan Coe-Renner, and Nicolas Ahn. We decided to pursue our collective interest in CNN’s and Machine Learning as a whole. We are working alongside our professor/academic advisor, Dr. Sepehr Amir-Mohammadian.
You can view a copy of the course overview, here.
As an overview, we will learn about:
- Using Pytorch in deep learning
- Tensors and their role in machine learning Fundamentals of training models and their validation
- Fundamentals of neural networks
- Convolutional neural networks and their role in image classification
- Data augmentation
- Image segmentation