N-grams
N-grams are contiguous sequences of n items (such as words, characters, or tokens) from a given text or speech sample, used primarily in computational linguistics and natural language processing (NLP). They model language patterns by analyzing the frequency and context of these sequences, enabling tasks like text prediction, spelling correction, and language modeling. This statistical approach helps capture local dependencies and predict the likelihood of sequences in data.
Developers should learn N-grams when working on NLP projects that require text analysis, such as building chatbots, search engines, or machine translation systems, as they provide a simple yet effective way to understand language structure and improve accuracy. They are particularly useful for tasks involving text generation, sentiment analysis, and information retrieval, where modeling word or character sequences is essential for predicting outcomes or identifying patterns in large datasets.