18. Athul SunilKumar

@18athulsunilkum Tasks: 83

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Joined: June 2024

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18. Athul SunilKumar's tools

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  SAM

  AI sentiment decoder for nuanced text analysis.

  Sentiment analysis

  Open
  29
  4
  Released 1y ago

  100% Free
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  # Sentiment Analysis Model ## Proposed Approach: 1. **Data Collection and Preparation** - Gather large dataset of labeled texts from diverse sources (social media, reviews, comments) - Include examples with sarcasm, enthusiasm, frustration, etc. - Clean and preprocess data (remove noise, normalize text) 2. **Model Architecture** - Use a pre-trained language model like BERT as the base - Fine-tune on sentiment classification task - Add classifier head to output sentiment and confidence 3. **Training** - Fine-tune on labeled sentiment dataset - Use cross-validation to evaluate performance - Optimize hyperparameters 4. **Evaluation** - Test on held-out test set - Evaluate accuracy, F1 score, confusion matrix - Analyze performance on different text lengths, domains, tones 5. **Deployment** - Package model for easy deployment - Create API for sentiment predictions - Return sentiment label and confidence score 6. **Continuous Improvement** - Gather user feedback - Retrain periodically on new data - Fine-tune for specific domains as needed This approach should yield a robust sentiment model capable of handling diverse texts and tones while providing both sentiment labels and confidence scores.