About this document
Understanding N-grams in Language Modeling by Yogansh Kesharwani is a document available to read on EtoBox.
The document introduces n-gram language models and discusses how to estimate n-gram probabilities. It explains that n-gram models assign a probability to a sequence of words based on the probability of each word given the previous n-1 words. This is done using the chain rule of probability and the Markov assumption that the probability of a word depends only on the previous n-1 words. The document also discusses evaluating language models using perplexity, which measures how well a model predicts words in a
- Author
- Yogansh Kesharwani
- Language
- EN