Word Embeddings in NLP

4 hours of instruction

This course covers the intermediate concepts of natural language processing like creating word embeddings, feature engineering and word embeddings for finding text features for model development.

OBJECTIVES

1. Understand feature engineering in text analysis
2. Create word embeddings and learn to use pre-trained embeddings like GloVe
3. Compute text similarity based on the embeddings

PREREQUISITES

Topic Modeling in NLP

SYLLABUS & TOPICS COVERED

1. Word Embeddings
   • Feature engineering in text analysis
   • Word embeddings: creating new ones vs using pre-trained

SOFTWARE REQUIREMENTS

You will have access to a Python-based JupyterHub environment for this course. No additional download or installation is required.