Part 3: Natural Language Processing and Attention Mechanisms

Natural language processing (NLP) is a crucial foundation for understanding the Transformer model. Furthermore, as the Transformer relies heavily on the attention mechanism, an understanding of its principles is essential for comprehending the model’s architecture.

In the following chapters, we will begin by exploring the datasets commonly used in machine translation and the fundamental preprocessing techniques employed for handling natural language on computers.

Next, we will delve into the two primary language models: the n-gram model and the RNN-based language model.

Following these explanations, we will explore the two main tasks of NLP: Sequence Classification and Machine Translation.

Finally, we will delve into the attention mechanism in detail and introduce its application to sequence classification and machine translation tasks.