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DataEval

  • Overview
  • Installation Guide
  • Tutorials
  • How-to Guides
  • Concepts
    • Workflows
    • Glossary
    • API Reference
    • Contributing to DataEval
    • DataEval Change Log
    • About
  • Overview
  • Installation Guide
  • Tutorials
  • How-to Guides
  • Concepts
  • Workflows
  • Glossary
  • API Reference
  • Contributing to DataEval
  • DataEval Change Log
  • About

Section Navigation

  • Drift Detection Tutorial Using Multiple Drift Detectors
  • Out-of-Distribution (OOD) Detection Tutorial
  • Clustering Tutorial
  • Dataset Deduplication Tutorial
  • Dataset Linting Tutorial
  • Bayes Error Rate Estimation Tutorial
  • HP Divergence Estimation Tutorial
  • Class Parity Label Analysis Tutorial
  • Coverage
  • Dataset Sufficiency Analysis for Classification Tutorial
  • Dataset sufficiency Analysis for object detection Tutorial
  • Autoencoder Trainer
  • How-to Guides

How-to Guides#

These guides demonstrate more in-depth features and customizations of DataEval features for more advanced users.

In addition to viewing them in our documentation, these notebooks can also be opened in Google Colab to be used interactively!

Detectors#

  • How to detect if the data distribution is changing Open In Colab

  • How to monitor for outliers during deployment Open In Colab

  • How to identify outliers and/or anomalies in a dataset Open In Colab

  • How to detect duplicates in a dataset Open In Colab

  • How to identify poor quality images in a dataset Open In Colab

Metrics#

  • How to determine if a dataset can meet performance requirements Open In Colab

  • How to compare data distributions between 2 datasets Open In Colab

  • How to compare label distributions between 2 datasets Open In Colab

  • How to detect undersampled data subsets Open In Colab

Workflows#

  • How to determine the amount of data needed to meet image classification performance requirements Open In Colab

  • How to determine the amount of data needed to meet object detection performance requirements

Models#

  • How to create image embeddings with an autoencoder Open In Colab

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Drift Detection Tutorial Using Multiple Drift Detectors

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