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Project Title: Sentix AI: Global Sentiment Intelligence
Results & Impact:
1. Achieved a 92% F1-score by implementing domain-specific fine-tuning on diverse consumer datasets, ensuring high reliability in classification.
2. Engineered an Aspect-Based Sentiment Analysis (ABSA) module that decomposed reviews into granular attributes (performance, pricing, reliability), making trend tracking 15% more precise.
3. Optimized inference performance by 25% through model distillation and Docker-based containerization, enabling the system to handle thousands of concurrent requests.
4. Mitigated data bias by designing a robust pre-processing workflow including lemmatization and custom noise reduction, critical for handling global marketplace jargon.
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DO SUPPORT GUYS 😊
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