https://github.com/ayushverma135/sentixanalyzer

an NLP-powered sentiment analysis project to analyze text data and produces number of tokens in the language, keywords, polarity and subjectivity of the context. By classifying text as positive, negative, or neutral.
https://github.com/ayushverma135/sentixanalyzer

flask machine-learning natural-language-processing nlp python

Last synced: 4 days ago
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an NLP-powered sentiment analysis project to analyze text data and produces number of tokens in the language, keywords, polarity and subjectivity of the context. By classifying text as positive, negative, or neutral.

• Host: GitHub
• URL: https://github.com/ayushverma135/sentixanalyzer
• Owner: Ayushverma135
• Created: 2023-09-26T05:58:08.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2024-04-25T19:53:23.000Z (7 months ago)
• Last Synced: 2024-04-25T20:53:21.739Z (7 months ago)
• Topics: flask, machine-learning, natural-language-processing, nlp, python
• Language: HTML
• Homepage:
• Size: 174 KB
• Stars: 0
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# NLP-Sentiment-analysis-using-Machine-Learning-and-flask

Utilizing Natural Language Processing (NLP) techniques, this project employs machine learning algorithms to perform sentiment analysis on textual data. Implemented with Flask, a Python web framework, it provides a user-friendly interface for inputting text and receiving sentiment predictions in real-time. By combining the power of NLP and machine learning with the simplicity of Flask, this project offers a seamless solution for analyzing and understanding the sentiment expressed in text.