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: about 2 months 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 (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2024-04-25T19:53:23.000Z (about 2 years ago)
- Last Synced: 2025-01-01T02:13:34.289Z (over 1 year ago)
- Topics: flask, machine-learning, natural-language-processing, nlp, python
- Language: HTML
- Homepage:
- Size: 175 KB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0
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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.