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What is Natural Language Processing? Definition and Examples

types of nlp

Natural language processing works by taking unstructured data and converting it into a structured data format. For example, the suffix -ed on a word, like called, indicates past tense, but it has the same base infinitive (to call) as the present tense verb calling. Natural Language Processing (NLP) refers to a branch of Artificial Intelligence (AI) in Computer Science that gives computers the ability to analyze and interpret human language.

It involves retraining the model with gender-neutral language and balanced data to reduce biases in search results and recommendations. This code snippet types of nlp demonstrates a text data augmentation technique by replacing words with synonyms. This code simulates bias in generative AI for hiring recommendations.

Language Processing?

For example, consider the following string containing multiple delimiters such as comma, semi-colon, and white space. Finally we have a count based or TF-IDF matrix and the dependent variable (label) to develop the model. Further we can use these tokenized forms to count the number of words in a text or frequency of the words in a text. As mentioned above, data cleaning is basic but very important step in NLP.

Is as a method for uncovering hidden structures in sets of texts or documents. In essence it clusters texts to discover latent topics based on their contents, processing individual words and assigning them values based on their distribution. This technique is based on the assumptions that each document consists of a mixture of topics and that each topic consists of a set of words, which means that if we can spot these hidden topics we can unlock the meaning of our texts.

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The stemming or lemmatization NLP approach seeks to produce root words from these word variants. Most higher-level NLP applications involve aspects that emulate intelligent behaviour and apparent comprehension of natural language. More broadly speaking, the technical operationalization of increasingly advanced aspects of cognitive behaviour represents one of the developmental trajectories of NLP (see trends among CoNLL shared tasks above).

types of nlp

The main benefit of NLP is that it improves the way humans and computers communicate with each other. The most direct way to manipulate a computer is through code — the computer’s language. By enabling computers to understand human language, interacting with computers becomes much more intuitive for humans.


The earliest decision trees, producing systems of hard if–then rules, were still very similar to the old rule-based approaches. Only the introduction of hidden Markov models, applied to part-of-speech tagging, announced the end of the old rule-based approach. As you can see in the example below, NER is similar to sentiment analysis. NER, however, simply tags the identities, whether they are organization names, people, proper nouns, locations, etc., and keeps a running tally of how many times they occur within a dataset. In this manner, sentiment analysis can transform large archives of customer feedback, reviews, or social media reactions into actionable, quantified results.

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That is the reason why humans can easily and readily fetch the meaning of any word in any language in an instant, thanks to NLP. With global connectivity trending right now, the technique of natural language translation is a much needed tool that we need for various purposes. types of nlp It has advanced to such a level that machines everywhere are now using this technology to analyse data and carry out other functions as well. With humongous quantities of unstructured and unorganized data, NLP has helped big businesses to filter data and organize it well.

Understanding Bias in NLP Models

Chatbots have become a revolutionary step in the realm of technological advancement as they have left behind the human race when it comes to communication. With the help of a set of algorithms, https://www.metadialog.com/ robots can communicate with humans and get things done in no time. For instance, an example of a chatbot application is uber is supported by AI and serves its customers through ML chatbots.

types of nlp

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