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README.md

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+---
+language: en
+library_name: joblib
+tags:
+  - text-classification
+  - embeddings
+  - business
+  - data-engineering
+---
+
+# Business Issue Allocation Classifier
+
+A text classifier that maps a natural language business problem description to the most likely data engineering solution category.
+
+## Model Details
+
+- **Classifier:** SVM (Support Vector Machine)
+- **Embedding model:** `sentence-transformers/all-mpnet-base-v2`
+- **Classes:** 9 (stream_processing, etl_pipeline, data_warehouse, data_lake, api_integration, ml_feature_store, data_caching, data_governance, data_quality)
+- **Accuracy:** 88.2%
+- **Macro F1:** 88.4%
+
+## How to Use
+
+Clone the full project from GitHub and run:
+
+```python
+from src.inference import Predictor
+predictor = Predictor()
+result = predictor.predict("We need to detect fraud before transactions are approved.")
+print(result["predicted_label"])
+```
+
+## Dataset
+
+[dianamikova/business-issue-allocation](https://huggingface.co/datasets/dianamikova/business-issue-allocation)
+
+## GitHub
+
+[github.com/dianamikova/business-issue-allocation](https://github.com/dianamikova/business-issue-allocation)