What is bigram

Bigrams are a type of machine learning algorithm used to identify patterns in large datasets. They are used to find correlations between different words or phrases in a text. A bigram is a pair of two consecutive words in a given text. For example, the phrase “machine learning” would be a bigram.

Bigrams are commonly used in natural language processing (NLP) applications. They can be used to analyze the frequency of certain words or phrases in a given text. This can help identify topics, themes, and other trends in the text.

Bigrams can also be used to create features for machine learning models. For example, a bigram can be used to create a feature that captures the context of a sentence. This can help improve the accuracy of a model.

Bigrams can also be used to detect anomalies in a dataset. For example, a bigram can be used to detect rare words or phrases that may indicate a potential issue.

Bigrams can also be used to create word embeddings. Word embeddings are vector representations of words that capture the context of a sentence. These embeddings can be used to improve the accuracy of machine learning models.

Overall, bigrams are a powerful tool that can be used to identify patterns in large datasets. They can be used to improve the accuracy of machine learning models and detect anomalies in a dataset. Bigrams can also be used to create word embeddings which can improve the accuracy of machine learning models.