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| courses:xai:lab1 [2023/11/06 09:11] – [Resouurces] admin | courses:xai:lab1 [2024/11/25 07:33] (current) – admin |
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| ====== Lab 1: Introduction to working environment, basics of data manipulation and visualization ====== | ====== Lab 1: Introduction to working environment, basics of data manipulation and visualization ====== |
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| ===== Resouurces ===== | ===== Resources ===== |
| * Google Colab Notebook: [[https://colab.research.google.com/drive/1_3I1eIbo9tSkWRXeRTbfAYwUAwFR9bYU?usp=sharing|Colab]] | * Google Colab Notebook: [[https://colab.research.google.com/drive/1_3I1eIbo9tSkWRXeRTbfAYwUAwFR9bYU?usp=sharing|Colab]] |
| * Datasets: | * Datasets: |
| * Jigsaw dataset {{ :courses:xai:jigsaw-snapshot-data.zip |}} | * Jigsaw dataset {{ :courses:xai:jigsaw-snapshot-data.zip |}} |
| * Additional reading: | * 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 | * [[https://browse.arxiv.org/pdf/1901.10002.pdf|A Framework for Understanding Sources of Harm throughout |
| the Machine Learning Life Cycle]] | 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]] |
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