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Enterprise-grade NER with spaCy

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Named Entity Recognition is one of the most important and widely used NLP tasks. It's the method of extracting entities (key information) from a stack of unstructured or semi-structured data. An entity can be any word or series of words that consistently refers to the same thing. Every detected entity is classified into a predetermined category. For example, a NER model might detect the word "India" in a text and classify it as a "Country".



Natural Language in Python using spaCy: An Introduction

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This article provides a brief introduction to natural language using spaCy and related libraries in Python. The complementary Domino project is also available. This article and paired Domino project provide a brief introduction to working with natural language (sometimes called "text analytics") in Python using spaCy and related libraries. Data science teams in industry must work with lots of text, one of the top four categories of data used in machine learning. Think about it: how does the "operating system" for business work?


Comparison of Top 6 Python NLP Libraries

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Natural language processing (NLP) is getting very popular today, which became especially noticeable in the background of the deep learning development. NLP is a field of artificial intelligence aimed at understanding and extracting important information from text and further training based on text data. The main tasks include speech recognition and generation, text analysis, sentiment analysis, machine translation, etc. In the past decades, only experts with appropriate philological education could be engaged in the natural language processing. Besides mathematics and machine learning, they should have been familiar with some key linguistic concepts.


Getting Started with 5 Essential Natural Language Processing Libraries - KDnuggets

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Let's say that you have an understanding of how to tackle natural language processing tasks. Let's also say that you have decided, more specifically, the type of approach you will employ in attempting to solve your task. You still need to put your plan into action, computationally, and there is a good chance you will be looking to leverage an existing NLP library to help you do so. Assuming you are programming in Python (I can't help you if not), there is quite a landscape of options to choose from. While this article is not an endorsement of any particular collection of such solutions, it serves as an overview to a curated list of 5 popular libraries you may look to in order to work on your problems.