Feature Extraction
Sentiment Analysis
Classify text sentiment using DistilBERT with positive, negative, and neutral labels
Why do anything?
Understanding content sentiment enables filtering and analysis. Manual labeling doesn't scale.
Why now?
Customer feedback, reviews, and social content need automated sentiment analysis.
Why this feature?
DistilBERT-based sentiment classification with confidence scores and multi-class support.
How It Works
Sentiment classifier uses DistilBERT for text sentiment analysis.
1
Text Processing
Tokenize and prepare text for model
2
Classification
DistilBERT generates sentiment logits
3
Label Assignment
Convert logits to labels with confidence
Why This Approach
DistilBERT provides good accuracy with fast inference. Pre-trained on sentiment tasks.
Where This Is Used
Integration
client.collections.create(feature_extractor={"feature_extractor_name": "sentiment_classifier", "version": "v1"})