NLP Tools Documentation

This section provides an overview of the Natural Language Processing (NLP) tools available on our platform. Whether you're a beginner or an experienced user, these tools are designed to help you analyze, understand, and generate natural language content.

Available Tools

Text Analysis: Analyze sentiment, extract entities, and perform keyword extraction.
Language Detection: Identify the language of a given text.
Translation: Translate text from one language to another.
Summarization: Generate summaries of longer texts.

Usage

To use any of these tools, simply visit our NLP tools page.

Examples

Sentiment Analysis

Here's an example of sentiment analysis on a sentence:

import nlp_tools

text = "I love this product!"
result = nlp_tools.sentiment_analysis(text)
print(result)

Language Detection

To detect the language of a text:

import nlp_tools

text = "Je suis content de l'outil NLP."
result = nlp_tools.language_detection(text)
print(result)

Translation

For translating text:

import nlp_tools

text = "How are you?"
target_language = "es"
result = nlp_tools.translate(text, target_language)
print(result)

Summarization

Summarizing a longer text:

import nlp_tools

text = "Natural Language Processing (NLP) is a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large amounts of natural language data."
result = nlp_tools.summarize(text)
print(result)

Conclusion

NLP tools are a powerful way to process and analyze natural language data. We hope you find these tools helpful in your projects!