Twitter Sentiment Analysis
NLP platform with 88.3% ROC-AUC analyzing 400K tweets for brand monitoring and market intelligence
Technology Stack
Logistic RegressionSVMNaive BayesRandom ForestPyTorchLSTMTF-IDFStreamlit
ML Frameworks
Deep Learning
NLP
Deployment
ROI
$200K-$500K annual savings
Key Performance Indicators
Accuracy
80.3%Training Time
<5 minutesResponse Time Reduction
24h → 2h (92%)Business Impact Summary
| Return on Investment | $200K-$500K annual savings |
| Accuracy | 80.3% |
| Training Time | <5 minutes |
| Response Time Reduction | 24h → 2h (92%) |
Overview
Production-grade sentiment analysis platform with multiple ML approaches (traditional + deep learning) classifying tweet sentiment with 88.3% ROC-AUC. Real-time predictions with confidence scores for brand monitoring.
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