In this tutorial we will cover basic encoder-decoder models for neural sequence prediction models as used in tasks like translation, image captioning, and speech recognition. We will go over different architecturs for representing sequences including RNNs, CNNs, and self-attentional transformers, different attention models, training objectives, and inference algorithms.