CST 499 - Week 6
Hey everyone, This week, I made solid progress in my fast.ai studies while also applying what I learned toward my project work. I covered several advanced topics including Stable Diffusion, matrix multiplication, mean shift clustering, backpropagation, MLPs, autoencoders, and the fast.ai learner framework. These topics helped me better understand both the theory and implementation of deep learning models. This week, I focused on strengthening the foundational components of my project. I worked on understanding and implementing core neural network concepts, particularly backpropagation and matrix operations, which are essential for building and debugging models. I also explored the fast.ai learner framework and began setting up a structured training pipeline for my project. Additionally, I experimented with autoencoders to better understand representation learning, which may be useful for my project depending on how I structure my model. ...