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Rapid Keyword Extraction (RAKE) Algorithm in Natural Language Processing

Analytics Vidhya

Rapid Automatic Keyword Extraction(RAKE) is a Domain-Independent keyword extraction algorithm in Natural Language Processing. It is an Individual document-oriented dynamic Information retrieval method. Concept of RAKE is built on three matrices Word Degree (deg(w)), Word Frequency (freq(w)), Ratio of […].

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Natural Language Processing to Detect Spam Messages

Analytics Vidhya

To detect spam users, we can use traditional machine learning algorithms that use information from users’ tweets, demographics, shared URLs, and social connections as features. […]. The post Natural Language Processing to Detect Spam Messages appeared first on Analytics Vidhya.

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Natural Language Processing (NLP)

Dataconomy

Natural Language Processing (NLP) is revolutionizing the way we interact with technology. By enabling computers to understand and respond to human language, NLP opens up a world of possibilitiesfrom enhancing user experiences in chatbots to improving the accuracy of search engines.

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Natural language processing (NLP)

Dataconomy

Natural language processing (NLP) is a fascinating field at the intersection of computer science and linguistics, enabling machines to interpret and engage with human language. What is natural language processing (NLP)? Machine translation: Enabling the automatic translation of languages.

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The Resume Parser for Extracting Information with SpaCy’s Magic

Analytics Vidhya

By automating the initial screening of resumes using SpaCy‘s magic , a resume parser acts as a smart assistant, leveraging advanced algorithms and natural language processing techniques […] The post The Resume Parser for Extracting Information with SpaCy’s Magic appeared first on Analytics Vidhya.

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Extracting Medical Information From Clinical Text With NLP

Analytics Vidhya

One of the most promising areas within AI in healthcare is Natural Language Processing (NLP), which has the potential to revolutionize patient care by facilitating more efficient and accurate data analysis and communication.

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How to Learn Math for Data Science: A Roadmap for Beginners

KDnuggets

But you do need to understand the mathematical concepts behind the algorithms and analyses youll use daily. Part 2: Linear Algebra Every machine learning algorithm youll use relies on linear algebra. Understanding it transforms these algorithms from mysterious black boxes into tools you can use with confidence.

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