Sofia Reyes

Automated hiring tools are widely used and rarely audited by anyone outside the vendor. This project builds an independent auditing toolkit that labor and civil-rights organizations can run themselves, without needing access to a vendor's internal model.

Machine Learning covers the core supervised and unsupervised learning methods, how to evaluate them honestly, and where they tend to fail. Every technique is paired with a discussion of its assumptions, so students learn to ask what a model actually knows, not just what it outputs.

Deep Learning & Neural Networks goes past the introductory treatment in CSC304 into architectures for images, sequences, and beyond, along with the practical craft of actually training these models: initialization, regularization, and diagnosing why a network refuses to learn.