Neural Nets for NLP 2019 - Attention

This course covers the topic of Attention in Neural Networks for Natural Language Processing (NLP). The learning outcomes include understanding different types of attention mechanisms, improvements to attention, and specialized attention varieties. Students will learn about encoder-decoder models, calculating attention, attention score functions, and incorporating markov properties. The teaching method involves lectures and a case study on "Attention is All You Need." This course is intended for students interested in neural networks, NLP, and machine learning.