Foundations of Scalable Natural Language Processing

May 25, 2021 09:00 AM (PT)

Learn the fundamentals of natural language processing (NLP) and how to scale it as you solve classification, sentiment analysis, and text wrangling tasks. We will cover how to perform distributed model inference and hyperparameter search, as well as build distributed NLP models. Working through code examples and assignments in Python, students will learn how to use dimensionality reduction techniques, apply pre-trained word embeddings, leverage MLflow for experiment tracking and model management, and apply NLP models to massive datasets with Pandas UDFs. 

Prerequisites:

  • Experience programming in Python


Role: Data Scientist

Duration: Half-day

Labs: Yes