AI News, Comparison of Top 6 Python NLP Libraries

Comparison of Top 6 Python NLP Libraries

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.

Today, we want to outline and compare the most popular and helpful natural language processing libraries, based on our experience.

To make a comparison more vivid, we prepared a table that shows the pros and cons of the libraries.

Natural Language Processing With Python and NLTK p.1 Tokenizing words and Sentences

Natural Language Processing is the task we give computers to read and understand (process) written text (natural language). By far, the most popular toolkit or ...

R and OpenNLP for Natural Language Processing NLP - Part 2

Part 2 of the OpenNLP and R series focusing on Entity Extraction and Named Entity Recognition. Overview and demo of using Apache OpenNLP library in R to ...

Natural Language Understanding at Scale with Spark Native NLP, Spark ML &TensorFlow with Alex Thomas

"Natural language processing is a key component in many data science systems that must understand or reason about text. Common use cases include ...

Natural Language Processing with PySpark

Ready to move beyond Word Count? Watch as John Hogue walks through a practical example of a data pipeline to feed textual data for tagging with PySpark ...

R and OpenNLP for Natural Language Processing NLP - Part 1

Overview and demo of using Apache OpenNLP library in R to perform basic Natural Language Processing (NLP) tasks like string tokenizing, word tokenizing, ...

Stanford Core NLP Java Example | Natural Language Processing

This video covers Stanford CoreNLP Example. GitHub link for example: Stanford Core NLP: ..

Introduction to Natural Language Processing with Python - Barbara Fusinska

Natural Language Processing techniques allow addressing tasks like text classification and information extraction and content generation. They can give the ...

Lev Konstantinovskiy - Text similiarity with the next generation of word embeddings in Gensim

Description What is the closest word to "king"? Is it "Canute" or is it "crowned"? There are many ways to define "similar words" and "similar texts". Depending on ...

Text Classification - Natural Language Processing With Python and NLTK p.11

Now that we understand some of the basics of of natural language processing with the Python NLTK module, we're ready to try out text classification. This is ...