Quote: "Natural language processing (NLP) is an interdisciplinary subfield of computer science and linguistics."
The study of how computers can understand and generate human language. Natural Language Processing can be used to create more natural interactions in virtual environments.
Syntax: Understanding the structure of language and the relationships between words in a sentence.
Morphology: Studying the formation of words and their internal structure to better understand how they relate to one another.
Phonetics and phonology: Analyzing the sounds of spoken language and how they combine to form words, phrases, and sentences.
Semantics: Examining the meanings and relationships of words and phrases within a sentence and the wider context of linguistic communication.
Pragmatics: Understanding how context and external factors (such as cultural norms and social cues) affect the interpretation of language.
Cognitive linguistics: Investigating how humans process and acquire language, including the role of mental models, schemas, and prototypes.
Machine learning: Developing algorithms that can learn from data and make predictions or decisions based on patterns observed in that data.
Natural language generation: Creating software that can automatically produce human-like language in response to input from users or other sources.
Sentiment analysis: Identifying and categorizing emotions and opinions expressed in written or spoken language.
Text classification: Automatically categorizing large-scale textual data into meaningful categories based on its contents.
Named entity recognition: Identifying specific people, places, organizations, and other entities mentioned in text.
Information extraction: Automatically identifying and extracting relevant information from unstructured text data, such as news articles or social media posts.
Speech recognition: Converting spoken language into text or other digital output, making it easier to analyze and manipulate.
Language modeling: Developing statistical models that capture the complex patterns and relationships within natural language.
Deep Learning: Creating neural networks which can aid in language processing, topic modeling, and other aspects of natural language processing.
Sentiment Analysis: This type of NLP deals with extracting the subjective information from text data, such as the emotion, opinion, and mood of the writer.
Named Entity Recognition (NER): It is concerned with identifying and classifying named entities such as people, organizations, locations, and dates mentioned in the text.
Part-of-speech Tagging (POS): It identifies and labels every word in a sentence or text with its part of speech such as Noun, Verb, Adjective, Adverb or Pronoun.
Text summarization: It extracts the most important information from a lengthy or complex text document and presents it in a concise form.
Machine Translation: It is concerned with translating one language into another, either with the help of rule-based, statistical or deep learning based models.
Topic Modeling: It is a technique for extracting the underlying themes or patterns in a large corpus of text, by grouping them into clusters of related topics.
Question Answering (QA): It involves building systems to answer questions (usually in a natural language format) posed by humans or machines by extracting relevant information from sources of text.
Text Classification: It assigns labels or categories to text documents based on the content, such as identifying spam vs. non-spam messages or positive vs. negative sentiment.
Emotion Detection: It identifies the emotions expressed in text data by analyzing tone, word choice, sentence structure and other related factors.
Quote: "It is primarily concerned with giving computers the ability to support and manipulate speech."
Quote: "It involves processing natural language datasets, such as text corpora or speech corpora."
Quote: "It involves processing natural language datasets, such as text corpora or speech corpora, using either rule-based or probabilistic machine learning approaches."
Quote: "The goal is a computer capable of 'understanding' the contents of documents, including the contextual nuances of the language within them."
Quote: "The technology can then accurately extract information and insights contained in the documents as well as categorize and organize the documents themselves."
Quote: "Challenges in natural language processing frequently involve speech recognition, natural-language understanding, and natural-language generation."
Quote: "Natural language processing (NLP) is an interdisciplinary subfield of computer science and linguistics."
Quote: "Natural language processing (NLP) is an interdisciplinary subfield of computer science and linguistics."
Quote: "It is primarily concerned with giving computers the ability to support and manipulate speech."
Quote: "It involves processing natural language datasets, such as text corpora or speech corpora, using either rule-based or probabilistic machine learning approaches."
Quote: "The technology can then accurately extract information and insights contained in the documents."
Quote: "The goal is a computer capable of 'understanding' the contents of documents, including the contextual nuances of the language within them."
Quote: "The technology can then accurately extract information and insights contained in the documents as well as categorize and organize the documents themselves."
Quote: "It involves processing natural language datasets, such as text corpora or speech corpora, using either rule-based or probabilistic machine learning approaches."
Quote: "It involves processing natural language datasets, such as text corpora or speech corpora, using either rule-based or probabilistic machine learning approaches."
Quote: "Challenges in natural language processing frequently involve speech recognition, natural-language understanding, and natural-language generation."
Quote: "Natural language processing (NLP) is an interdisciplinary subfield of computer science and linguistics."
Quote: "It involves processing natural language datasets, such as text corpora or speech corpora."
Quote: "The technology can then accurately extract information and insights contained in the documents."