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Intent Classification

Notes on Intent Classification for ML platform / Applied AI interview preparation. The file index below shows what's in scope; click through to the individual notes for the depth.

Interview talking points

  • This is a sub-topic under Fine-Tuning-Foundational-Models. See the parent for the broader interview framing.

Files in this folder

File Title
01-business_weighted_error_score_mangaassist.md Business-Weighted Error Score for Intent Routing — MangaAssist
01-cluster_based_new_intent_discovery_mangaassist.md Cluster-Based New-Intent Discovery from Rejected / OOD Traffic — MangaAssist
01-confidence_calibration_for_intent_routing_mangaassist.md Confidence Calibration for Fine-Tuned Intent Routing — MangaAssist
01-fine_tuning_dry_run_mangaassist.md Fine-Tuning Dry Run Document — Intent Classifier (DistilBERT) for MangaAssist
01-fine_tuning_numerical_worked_examples_mangaassist.md Numerical Worked Examples for Fine-Tuning — MangaAssist Intent Classifier
01-intent-classifier-fine-tuning.md 01. Intent Classifier Fine-Tuning — DistilBERT for MangaAssist
01-multi_intent_detection_mangaassist.md Multi-Intent Detection for Intent Routing — MangaAssist
01-ood_unknown_intent_detection_mangaassist.md OOD / Unknown Intent Detection for Intent Routing — MangaAssist
README.md Intent Classification — Folder Index

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