Quote: "Natural language processing (NLP) is an interdisciplinary subfield of computer science and linguistics."
Natural Language Processing involves teaching computers to understand and interpret human language. It is used in applications such as speech recognition, machine translation, and sentiment analysis.
Introduction to NLP: Overview of what natural language processing is, its applications, and how it works.
Text Preprocessing: Cleaning and preparing text data for analysis, including techniques like tokenization, stemming, and stop word removal.
Language Models: Statistical models used to predict the probability of a sequence of words in a language, including n-gram models and language models based on neural networks.
Named Entity Recognition: Identifying and categorizing named entities in text, such as people, organizations, and locations.
Part-of-Speech Tagging: Labeling each word in a sentence with its part of speech, such as noun, verb, or adjective.
Parsing: Analyzing the grammatical structure of sentences, including techniques like dependency parsing and constituency parsing.
Sentiment Analysis: Detecting and classifying the emotional sentiment expressed in a piece of text.
Topic Modeling: Discovering the underlying themes or topics in a collection of documents.
Word Embeddings: Representing words as vectors in a high-dimensional space, where words with similar meanings are close together.
Sequence-to-Sequence Modeling: Models that can translate one sequence of text into another, such as machine translation or text summarization.
Attention Mechanisms: A type of neural network architecture that allows models to focus on specific parts of the input when making predictions.
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."