# Tutorials


These tutorials demonstrate how to use {term}`DataEval` to perform data analysis tasks using
various detectors, metrics and workflows to assess the suitability of a dataset and/or model.

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

Data Engineering Stage
- [Data Cleaning Guide](EDA_Part1) [![Open In Colab][colab-badge]][eda-colab]
- [Assessing the Data Space Guide](EDA_Part2) [![Open In Colab][colab-badge]][dataspace-colab]
- [Identifying Bias and Correlations Guide](EDA_Part3) [![Open In Colab][colab-badge]][bias-colab]

Monitoring Stage
- [Data Monitoring Guide](Data_Monitoring.ipynb) [![Open In Colab][colab-badge]][monitoring-colab]

:::{toctree}
:hidden:
:maxdepth: 1

EDA_Part1.ipynb
EDA_Part2.ipynb
EDA_Part3.ipynb
Data_Monitoring.ipynb
:::

[colab-badge]: https://colab.research.google.com/assets/colab-badge.svg
[eda-colab]: https://colab.research.google.com/github/aria-ml/dataeval/blob/v0.73.1/docs/tutorials/EDA_Part1.ipynb
[dataspace-colab]: https://colab.research.google.com/github/aria-ml/dataeval/blob/v0.73.1/docs/tutorials/EDA_Part2.ipynb
[bias-colab]: https://colab.research.google.com/github/aria-ml/dataeval/blob/v0.73.1/docs/tutorials/EDA_Part3.ipynb
[monitoring-colab]: https://colab.research.google.com/github/aria-ml/dataeval/blob/v0.73.1/docs/tutorials/Data_Monitoring.ipynb