Natural Language Processing
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Natural Language Processing
Natural Language Processing (acronym as “NLP”) is a field of computer science that gives computers the ability to understand and process human language.
NLP is used in a wide variety of applications, including Machine Translation, Chatbots, and Text Analysis.
A language model is the core component of modern Natural Language Processing (NLP). It’s a statistical tool that analyzes the pattern of human language for the prediction of words.
NLP based Language Models analyze bodies of text data to provide a basis for their word predictions. They are used in natural language processing (NLP) applications, particularly ones that generate text as an output.
Key Points of NLP
- NLP is a field of artificial intelligence. This means that it is a branch of computer science that focuses on developing algorithms and techniques for processing human language.
- NLP allows computers to understand and process human language. This means that NLP can be used to develop applications that can understand what humans are saying and writing, and can generate text that is understandable to humans.
- NLP is used in a variety of applications. These applications include Text Summarization, Machine Translation, and Chatbots.
Popular Programming Languages for NLP
Popular Python Libraries in NLP
Python is widely used in NLP due to its simplicity, readability, and vast ecosystem of NLP libraries such as NLTK, spaCy, and TensorFlow.
Popular R Libraries in NLP
R Studio offers packages like tm, quanteda, and tidytext, which provide functionality for text mining, sentiment analysis, and topic modeling.
Natural Language Toolkit (NLTK)
NLTK is a leading platform for building Python programs to work with human language data
It provides easy-to-use interfaces to over 50 corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries, and an active discussion forum
TensorFlow is an end-to-end platform for machine learning
TensorFlow is a popular choice for NLP tasks that involve machine learning, such as Machine Translation and Question-Answering.
Tensorflow supports:
Tensorflow supports:
- Multidimensional-array based numeric computation
- GPU and distributed processing
- Automatic differentiation
- Model construction, training, and export
NLP can be used for a variety of tasks, including:
Text Classification: This is the task of assigning a label to a piece of text, such as “spam” or “ham”
Named Entity Recognition: This is the task of identifying named entities in a piece of text, such as people, organizations, and locations
Part-of-speech tagging: This is the task of assigning a part-of-speech tag to each word in a piece of text, such as noun, verb, adjective, or adverb.
Sentiment analysis: This is the task of determining the sentiment of a piece of text, such as whether it is positive, negative, or neutral.
Machine translation: This is the task of translating text from one language to another using NLP techniques.
Question answering: This is the task of answering the questions in natural language. Corpus of document is used to extract the relevant answer using NLP algorithms
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