Machine Learning (ML) for Natural Language Processing - PowerPoint PPT Presentation

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Machine Learning (ML) for Natural Language Processing

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Natural Language Processing (NLP), Artificial Intelligence (AI), and Machine learning (ML) are certainly used interchangeably, so to differentiate among the three; you have to clarify the concepts. – PowerPoint PPT presentation

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Title: Machine Learning (ML) for Natural Language Processing


1
Machine Learning (ML) for Natural Language
Processing (NLP)
Natural Language Processing (NLP), Artificial
Intelligence (AI), and Machine learning (ML) are
certainly used interchangeably, so to
differentiate among the three you have to
clarify the concepts. First, you must know that
NLP and machine learning both are subsets of
Artificial Intelligence. You can also read
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India Things to know about Natural Language
Processing, Machine Learning and Artificial
Intelligence Natural Language Processing
(NLP) MLP is a branch of AI and an ML subfield
that enables computers to understand and process
human language. It aims to develop a system that
can automatically make sense of the text and
perform tasks like translation, spell check, and
topic classification. But to automate the above
duties and deliver accurate responses, you will
need machine learning.
2
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Guarantee Machine Learning (ML) Machine
learning applies algorithms that teach machines
how to learn and improve from previous
experiences without being distinctly programmed
to work automatically. Artificial Intelligence
(AI) AI is a descriptive term for machines that
can replicate human intelligence. AI is the
simulation of human intelligence in programmed
machines to think like humans and copy their
actions. The term AI can also be applied to any
machine that shows the characteristics of a human
mind, such as learning and problem-solving
ability. Conclusion Natural language
processing (NLP) and machine learning (ML) are
both integral parts of Artificial Intelligence
(AI). For example - AI chatbots, use NLP to
interpret what user say and what they expected to
do and ML to deliver more accurate responses
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