https://github.com/shrutakeerti/sentiment-analysis-info

The information gathered and can be used for the upcoming projects of Sentiment analysis
https://github.com/shrutakeerti/sentiment-analysis-info

deep-learning lstm nlp nlp-machine-learning opinion-mining

Last synced: 2 months ago
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The information gathered and can be used for the upcoming projects of Sentiment analysis

• Host: GitHub
• URL: https://github.com/shrutakeerti/sentiment-analysis-info
• Owner: Shrutakeerti
• Created: 2024-01-08T19:11:54.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-07-15T07:47:08.000Z (10 months ago)
• Last Synced: 2024-07-15T09:24:44.855Z (10 months ago)
• Topics: deep-learning, lstm, nlp, nlp-machine-learning, opinion-mining
• Language: Jupyter Notebook
• Homepage:
• Size: 29.9 MB
• Stars: 3
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
Sentiment Analysis Project

Overview

This sentiment analysis project aims to analyze and classify the emotions expressed in text data. By leveraging natural language processing techniques, the project seeks to categorize text into positive, negative, or neutral sentiments based on the language used.

Key Features

Text preprocessing: Includes tasks such as tokenization, stop-word removal, and stemming to clean the text data.

Sentiment classification: Utilizes machine learning algorithms like Naive Bayes, Support Vector Machines, or deep learning models like LSTM for sentiment classification.

Performance evaluation: Measures the accuracy, precision, recall, and F1 score of the sentiment analysis model to assess its effectiveness.