- Deep Learning

Catalog description

An introduction to deep learning. Deep learning is a powerful technique for finding patterns in data that has been the driving force behind the advancement of AI in the twenty-first century. Students will investigate the primary techniques that fall under the umbrella of deep learning as well as the underlying mathematics. Topics include probability, gradient descent, backpropagation, neural networks, recurrent neural networks, transformers, and large language models. Three hours of lecture and two hours of lab each week. In the labs, students will develop machine learning applications and experiment with those applications on real data.