Machine learning (ML) is the scientific study of algorithms and statistical models that computers use in order to perform a specific task effectively without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence. This course will cover advanced topics in machine learning such as deep learning, transfer learning, multiview learning, clustering and Interpretability of ML methods. Source
Professor: Majid Komeili
Grade: in progress
The course is primarily project-based, with two assignments as well as a major research project. The assignments focused on:
- Convolutional Neural Networks
For the research project, I chose to explore large-scale relevance matching using many thousands of Reddit comments and associated news article.
The course also included presentations of two conference papers from a variety of topics. I chose to focus on interpretability in deep learning, and will present the following two papers:
slides will be shared once available