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Aporia Documentation
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# Aporia Documentation
## V1
- [Welcome to Aporia!](https://docs.aporia.com/v1/welcome-to-aporia.md): Aporia is an ML observability platform that empowers ML teams to monitor and improve their models in production.
- [Quickstart](https://docs.aporia.com/v1/introduction/quickstart.md)
- [Support](https://docs.aporia.com/v1/introduction/support.md)
- [Why Monitor ML Models?](https://docs.aporia.com/v1/core-concepts/why-monitor-ml-models.md)
- [Understanding Data Drift](https://docs.aporia.com/v1/core-concepts/understanding-data-drift.md)
- [Analyzing Performance](https://docs.aporia.com/v1/core-concepts/analyzing-performance.md)
- [Tracking Data Segments](https://docs.aporia.com/v1/core-concepts/tracking-data-segments.md)
- [Models & Versions](https://docs.aporia.com/v1/core-concepts/model-versions.md)
- [Explainability](https://docs.aporia.com/v1/core-concepts/explainability.md)
- [Overview](https://docs.aporia.com/v1/storing-your-predictions/overview.md)
- [Real-time Models (Postgres)](https://docs.aporia.com/v1/storing-your-predictions/real-time-models-postgres.md)
- [Real-time Models (Kafka)](https://docs.aporia.com/v1/storing-your-predictions/real-time-models-kafka.md)
- [Batch Models](https://docs.aporia.com/v1/storing-your-predictions/batch-models.md)
- [Kubeflow / KServe](https://docs.aporia.com/v1/storing-your-predictions/kserve.md)
- [Logging to Aporia directly](https://docs.aporia.com/v1/storing-your-predictions/logging-to-aporia-directly.md)
- [Regression](https://docs.aporia.com/v1/model-types/regression.md)
- [Binary Classification](https://docs.aporia.com/v1/model-types/binary.md)
- [Multiclass Classification](https://docs.aporia.com/v1/model-types/multiclass-classification.md)
- [Multi-Label Classification](https://docs.aporia.com/v1/model-types/multi-label-classification.md)
- [Ranking](https://docs.aporia.com/v1/model-types/ranking.md)
- [Intro to NLP Monitoring](https://docs.aporia.com/v1/nlp/intro-to-nlp-monitoring.md): Whether it's text classification, information extraction, or question answering, use Aporia to monitor your Natural Language Processing models in production.
- [Example: Text Classification](https://docs.aporia.com/v1/nlp/example-text-classification.md)
- [Example: Token Classification](https://docs.aporia.com/v1/nlp/example-token-classification.md)
- [Example: Question Answering](https://docs.aporia.com/v1/nlp/example-question-answering.md)
- [Overview](https://docs.aporia.com/v1/data-sources/overview.md)
- [Amazon S3](https://docs.aporia.com/v1/data-sources/s3.md)
- [Athena](https://docs.aporia.com/v1/data-sources/athena.md)
- [BigQuery](https://docs.aporia.com/v1/data-sources/bigquery.md)
- [Delta Lake](https://docs.aporia.com/v1/data-sources/delta-lake.md)
- [Glue Data Catalog](https://docs.aporia.com/v1/data-sources/glue-data-catalog.md)
- [PostgreSQL](https://docs.aporia.com/v1/data-sources/postgresql.md)
- [Redshift](https://docs.aporia.com/v1/data-sources/redshift.md)
- [Snowflake](https://docs.aporia.c
…
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