====== Lab 1:  Introduction to working environment, basics of data manipulation and visualization ======

===== Resouurces =====
  * Google Colab Notebook: [[https://colab.research.google.com/drive/1_3I1eIbo9tSkWRXeRTbfAYwUAwFR9bYU?usp=sharing|Colab]]
  * Datasets:
    * Adult Dataset: {{ :courses:xai:adult.zip |}}
    * Jigsaw dataset {{ :courses:xai:jigsaw-snapshot-data.zip |}}
  * Additional reading:
    * [[https://developers.google.com/machine-learning/crash-course/fairness| Google Deveoper ML course: Fairness]]
    * [[https://browse.arxiv.org/pdf/1901.10002.pdf|A Framework for Understanding Sources of Harm throughout
the Machine Learning Life Cycle]]
    * [[https://ascpt.onlinelibrary.wiley.com/doi/10.1002/cpt.3117|Measurement and Mitigation of Bias in Artificial Intelligence: A Narrative Literature Review for Regulatory Science]]
    * [[https://dl.acm.org/doi/pdf/10.1145/3457607|A Survey on Bias and Fairness in Machine Learning]]
  * Tools
    * [[https://www.holisticai.com/blog/bias-mitigation-strategies-techniques-for-classification-tasks|Holistic AI Framework for bias mitigation]]
    * [[https://github.com/Trusted-AI/AIF360| IBM framework for bias measuring and removal]]