NLPShala , the best IDE for all Natural language processing tasks.

Natural language processing (NLP) is the ability of a computer program to understand human language as it is spoken and written which is referred to as natural language. It is a component of artificial intelligence.

Through NLPShala you can easily perform all NLP Task visually and with lots of customizations.

Introduction

NLPShala is an opensource project with provides NLP scientist a IDE through which they can perform all NLP tasks easily.

It's a solid platform for all beginner enthusiasts to learn NLP in python.

Various NLP pre builts functions are packed in this tool.

As a beginner student we often face much difficulty learning nlp core concepts. As programming without getting it visually doesn't develop much interest. While exploring many open source projects i didn't get any beginner friendly materials to get started with as we don't get much interest in learning the things. While if these goes visually then some interest gets developed.

The idea behind such a tool was to create something that can reduce repetitive code and also while keeping it beginner friendly.

Quick intro

Through NLPShala beginner's can learn NLP tasks easily that is without writing much code and for advanced programmers there is also a full robust library which contains all the required NLP tasks that can com handy in any project!

Just import the library and starts coding a nlp project and yes with pre built sets of APIs.

Dependencies

Various open source libraries such as TextBlob , SpaCy and NLTK have been used accordingly, and yes as a beginner this project will surely help in undernstanding these libraries and concepts that are used in all major NLP related tasks.

What's there

• Fully modern UI IDE.
• Plugable library that can be plugged into any project.
• Rest APIs prototypes to power your development.
• Beginner friendly docs.

Features

• Sentiment Analysis.
• Get synonym and antonym.
• Floating widgets to change required words easily.
• Get definitions of each word.
• Spacy Phrase Matcher.
• Summary generation.
• Most common words , Visualizations.
• Perfrom dependency parsing that is transition-based dependency parser component.
• Personalize accordingly.

Future development task

yes there is a lot more to build, Basically integrating all the remaining NLP operations into the project.