Explore attention mechanisms in neural networks for natural language processing in this comprehensive lecture from CMU's Neural Networks for NLP course. Delve into various aspects of attention, including what to attend to, improvements to attention techniques, and specialized attention varieties. Examine a case study on the "Attention is All You Need" paper, and learn about attention score functions, input sentence handling, multi-headed attention, and training tricks. Gain insights into incorporating Markov properties, supervised training for attention, and hard attention concepts. This in-depth presentation covers essential topics for understanding and implementing attention in NLP models.