Python Tutorials

The following tutorials are available in Google Colab. To freely edit and save your changes, make a copy of the notebook to your drive or download it to your machine.

• T01: Data Profiling

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  In this tutorial, we will focus on how data profiling fosters the Data-Centric AI paradigm. We'll be using the Adult Census Income Dataset, freely available on Kaggle or UCI Repository, and explore ydata-profiling.

  Open Notebook

• T02: Data Complexity

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  In this tutorial, we will discuss the basis of data complexity and meta-learning by exploring some popular open-source packages such as problexity, pymfe, and pyhard.

  Open Notebook

• T03: Imbalanced Data

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  In this tutorial, we explore the problem of class imbalance and some established techniques to surpass it, using imbalanced-learn.

  Open Notebook

• T04: Bias and Fairness

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  In this tutorial, we will explore bias and fairness, concepts on the Adult Census Income Dataset, using data-auditor and holisticai.

  Open Notebook

• T05: Missing Data

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  Work in progress.

  Coming Soon

• T06: Explainability

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  Work in progress.

  Coming Soon

• T07: Data Privacy and Synthetic Data

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  Work in progress.

  Coming Soon