Language modeling (natural language processing) is a fundamental task within computational linguistics and natural language processing focused on developing computational models that learn the statistical properties of human language. Specifically, it involves creating probabilistic models capable of predicting the likelihood of a sequence of words occurring together or estimating the probability of the next word in a sequence given the preceding words. These models capture the dependencies and structures within language from large text corpora. Language modeling is a core component underlying numerous NLP applications, including machine translation, speech recognition, text generation, information retrieval, and sentiment analysis, by providing a quantitative framework for assessing the linguistic plausibility or coherence of text.