This repository provides an interactive tutorial on applying deep learning to NLP problems, created for a Georgia Tech NLP class. It covers foundational topics including word embeddings, LSTMs, and sequence modeling, progressing to advanced structure prediction tasks like named-entity recognition using BiLSTM-CRF architectures. The material is designed to prepare students for implementing transition parsers using PyTorch’s dynamic computation graphs.