spacy

spaCy is an advanced open-source library designed for Natural Language Processing (NLP) in Python and Cython. Unlike other libraries, spaCy focuses on providing efficient and production-ready tools for text processing tasks. It excels in various NLP functions, including tokenization, part-of-speech tagging, named entity recognition (NER), and dependency parsing. With its ability to integrate deep learning workflows and support for multiple languages, spaCy is a powerful choice for developers and researchers alike. Its user-friendly interface and high performance make it an essential tool for anyone working with text data in a computational context.

So… What’s spaCy?

Towards Data Science

If a normal data analysis tool in Python for tabular and structured data has Pandas, then the data analysis tool in Natural Language Processing (NLP) for text and unstructured data has spaCy. When…

Train NER with Custom training data using spaCy.

Towards Data Science

SpaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython. The library is published under the MIT license and its main…

Python’s spacy library

Python in Plain English

Alright, fasten your seatbelts because we’re about to zoom into the world of spaCy, a powerful Python library that’s like a Swiss Army knife for text processing! 😄✨ Imagine you’re a detective 🕵️‍♂️,...

Practical Python: spaCy for NLP

Towards Data Science

spaCy is a powerful open-source library for natural language processing in Python. It includes advanced features for tokenization, named entity recognition, and part-of-speech tagging and is capable o...

Natural Language Processing with spaCy— Steps and Examples

Towards AI

spaCy is an open-source, advanced Natural Language Processing (NLP) library in Python. The library was developed by Matthew Honnibal and Ines Montani, the founders of the company Explosion.ai. In my…

Python Spacy : Knowing These Secrets Make U Utilize Library At Ease

Analytics Vidhya

SPACY is one of the open source library available in python which guarantees solution to NLP (Natural Language Processing) problem statement. It has three different language corpus available …

spaCy Basics

Towards Data Science

Learn to use the spaCy framework for NLP tasks including tokenization, part-of-speech tagging, lemmatization, and named entity recognition.

Machine Learning for Text Classification Using SpaCy in Python

Towards Data Science

spaCy is a popular and easy-to-use natural language processing library in Python. It provides current state-of-the-art accuracy and speed levels, and has an active open source community. However…

Complete Guideline to Implementation of Basic NLP Techniques with spaCy (Part-4)

Towards Data Science

SpaCy is fastest and efficient natural language processing library for python. It can performs tokenization, lemmatization, stop word removal, etc.

Reusable Terms with spaCy Rule Matcher

Towards Data Science

I’m not gonna lie, I really dig spaCy; it’s based on sophisticated natural language processing (NLP) but is incredibly simple to use. It’s an ML engineer’s dream (what a weird dream though)…

A couple tricks for using spaCy at scale

Towards Data Science

The Python package spaCy is a great tool for natural language processing. Here are a couple things I’ve done to use it on large datasets.

A Quick Guide to Tokenization, Lemmatization, Stop Words, and Phrase Matching using spaCy | NLP |…

Towards Data Science

“ spaCy” is designed specifically for production use. It helps you build applications that process and “understand” large volumes of text. It can be used to build information extraction or natural…