The chapter introduces fundamental algorithms and techniques in Natural Language Processing (NLP), focusing on regular expressions, text normalization, and edit distance. It begins with an introduction to regular expressions, explaining how they are used to specify patterns in text and perform substitutions. The chapter then delves into text normalization, which involves tokenization, lemmatization, and sentence segmentation. It discusses the importance of handling different languages, genres, and demographic characteristics of the text. The chapter also covers the Unix tools used for basic tokenization and normalization, and provides a detailed example of tokenizing Shakespeare's works using these tools. The section on edit distance explains how to measure the similarity between two strings based on the number of edits required to transform one into the other, which is crucial for tasks like spelling correction and speech recognition. Overall, the chapter lays the groundwork for understanding the foundational tools and techniques used in NLP.The chapter introduces fundamental algorithms and techniques in Natural Language Processing (NLP), focusing on regular expressions, text normalization, and edit distance. It begins with an introduction to regular expressions, explaining how they are used to specify patterns in text and perform substitutions. The chapter then delves into text normalization, which involves tokenization, lemmatization, and sentence segmentation. It discusses the importance of handling different languages, genres, and demographic characteristics of the text. The chapter also covers the Unix tools used for basic tokenization and normalization, and provides a detailed example of tokenizing Shakespeare's works using these tools. The section on edit distance explains how to measure the similarity between two strings based on the number of edits required to transform one into the other, which is crucial for tasks like spelling correction and speech recognition. Overall, the chapter lays the groundwork for understanding the foundational tools and techniques used in NLP.