This repository contains course materials for an Applied Natural Language Processing class taught at UC Berkeley in Spring 2019. The materials include Jupyter notebooks covering text classification, sentiment analysis using dictionaries and word embeddings, distributional similarity methods, tokenization experiments, regularization for regression, and hypothesis testing. It serves as a practical introduction to NLP techniques and statistical evaluation methods.