How Natural Language Processing (NLP) Works With Machine Learning

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Business analysts use ML too positively or negatively for scaling progressive graphs. Datasets may be low in features or low sparse which in turn are unable to fully use the ML algorithms.

NLP is part (subset) of Artificial Intelligence which is a subfield of computer science. Data Science Problem Process

  • Preprocessing (Cleaning Data)
  • Feature Engineering
  • Implementation Of Model
  • Training Phase
  • Testing

Is Natural Language Processing Machine Learning?

No, NLP is one of the important part of data science. We can consider it a bridge between machine earning and linguistics. They all will use the same algorithms, programming languages, computational power, and statistical tools.

Is ML the Opposite of Natural Language Processing?

The difference between both is quite a long debate. Machine Learning is the process of analysis of data and prediction of results based on the dataset without human interaction. Some applications are Fraud analysis, self-driving cars, stock exchange, and NLP. A combination of AI with written text analysis makes a separate branch named as NLP.

How Is Machine Learning Used in Natural Language Processing?

There are a lot of applications almost in every field including engineering, medicine, digital marketing, and search engine. Many applications of ML are given below


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