Large Language Models in Python (Session 3)
In this 3-session seminar, we will delve into neural network/deep learning approaches that have become dominant in NLP in recent years. The course will cover concepts in the rapidly evolving state-of-the-art, with a focus on transfer learning using pretrained language models and transformers such as BERT and GPT. Participants will leverage these models off the shelf to accomplish tasks like translation and zero-shot classification. Additionally, we will explore the functioning of hyperparameters and learn how to train these models for specialized tasks. All sessions will be conducted in Python, and code walkthroughs will be provided to help participants grasp the implementation of these models. Participants are expected to have a basic proficiency in Python and building machine learning models tasks that use text data.
This class will be fully in-person, and participants will use their own laptops. Enrollment is limited to 20.
