NLP Application: Named Entity Recognition (NER) in Python with Spacy

Natural Language Processing deals with text data. The amount of text data generated these days is enormous. And, this data if utilized properly can bring many fruitful results. Some of the most important Natural Language Processing applications are Text Analytics, Parts of Speech Tagging, Sentiment Analysis, and Named Entity Recognition. The vast amount of text data contains a huge amount of information. An important aspect of analyzing these text data is the identification of Named Entities. What is a Named […]

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Part 10: Step by Step Guide to Master NLP – Named Entity Recognition

This article was published as a part of the Data Science Blogathon Introduction This article is part of an ongoing blog series on Natural Language Processing (NLP). In the previous article, we discussed semantic analysis, which is a level of NLP tasks. In that article, we discussed the techniques of Semantic analysis in which we discussed one technique named entity extraction, which is very important to understand in NLP. So, In this article, we will deep dive into the entity extraction […]

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Introduction to Computational Linguistics and Dependency Trees in data science

Introduction In recent years, the amalgam of deep learning fundamentals with Natural Language Processing techniques has shown a great improvement in the information mining tasks on unstructured text data. The models are now able to recognize natural language and speech comparable to human levels. Despite such improvements, discrepancies in the results still exist as sometimes the information is coded very deep in the syntaxes and syntactic structures of the corpus. Example – Problem with Neural Networks For example, a conversation […]

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