What is stop word removal? Stop words are commonly used words that have very little meaning, such as "a," "an," "the," or "in." Stopwords are typically excluded from natural language processing...

What is stop word removal? Stop words are commonly used words that have very little meaning, such as "a," "an," "the," or "in." Stopwords are typically excluded from natural language processing...
Lemmatization is the conversion of a word to its base form or lemma. This differs from stemming, which takes a word down to its root form by removing its prefixes and suffixes. Lemmatization, on the...
Tokenization is a process in natural language processing (NLP) where a piece of text is split into smaller units called tokens. This is important for a lot of NLP tasks because it lets the model...
What is Named Entity Recognition (NER)? Named entity recognition (NER) is a part of natural language processing (NLP) that involves finding and classifying named entities in text. Named entities are...
Text summarization is so prominent in natural language processing (NLP) that it made our top ten list of NLP techniques to know. Natural Language Processing (NLP) text summarization has a sizable...
Word embedding is used in natural language processing (NLP) to describe how words are represented for text analysis. Typically, this representation takes the form of a real-valued vector that...
What is the curse of dimensionality? When dealing with high-dimensional data, several issues are known as the "Curse of Dimensionality." A dataset's quantity of attributes or features is called the...
Tf-idf is a way to measure the importance of a word. It is one of the ten most commonly used natural language processing techniques. This comprehensive guide covers tf-idf, why you should use it,...
Natural language processing is a subfield of machine learning and information retrieval that focuses on processing textual data. There are many different natural language processing techniques,...
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