NLP: Python Tools and Libraries
* Before reading through our piece on common Python tools and libraries, make sure to check out the previous four installments of this series: “Common NLP Techniques,” “What is Natural Language Processing,” “Natural Language Processing Applications, and “What are the Top NLP Language Models.”
What’s this about: Natural language processing (NLP) is focused on training data models with insights extracted from text. As covered in the previous installment of this series, NLP is used for applications like sentiment analysis, named entity recognition, and text summarization. With the wide range of NLP tools and libraries that are now available to developers, the range of NLP applications are also being expanded. These libraries are crucial for anyone looking to develop technologies like chatbots, speech recognition, and patient data processing.
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What is an NLP Library?
An NLP library has one fundamental goal: to simplify text processing. The best libraries can convert text into structured features, which can then be fed into machine learning (ML) and deep learning (DL) systems.
NLP libraries changed the game for NLP. Previously, these types of projects required professionals with a deep level of expertise in the areas of mathematics, machine learning…
