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Natural Language Processing - Coggle Diagram
Natural Language Processing
What is Natural Language Processing -NLP
Natural Language Processing strives to make machines which understand and respond to text, voice data and respond with text, speech same ways as humans.
Applications of NLP
Text Summarization
Email Filtering
Automated Reasoning
Chatbots
Targeted Advertising
Machine Learning
Machine Learning is science of getting computers to act without being
Advantages
Improved Accuracy and Precision
Automation of tasks
Predective analysis
Adaptability
Very cost effective with automation of certain tasks
Disadvantages
Dependency on data
Machine learning model can be vulnerable to security threats
Maintenance and monitoring can be resource intensive
Ethical and privacy concern
History of NLP-Natural Language Processing
Turning tests in 1950 as proposed by Alan Turning
First NLP System Georgetown-IBM Experiment (1954)
Development of Linguistic Theories from 1970-1980
Introduction of Machine Learning in 1990
Advancements in machine learning in 2000
Deep learning revolution in 2010
Fields in NLP
Syntax
This studies the structure of sentences, parses and grammar analysis.
Semantics
This studies the meaning of language like word senses clear up semantic role labeling
Named Entity Recognition (NER)
Identifying and classifying entities in text like a person name, location, organization,etc.
Tools and libraries in NLP
Natural Language Toolkit - NLTK
Gensim
CoreNLP
OpenNLP