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In this month's AI 101, we're learning about differential privacy and federated learning. Try you hand at it in this Google Colab Tutorial: https://colab.research.google.com/drive/11jAZ5Xb4UAhO5IMVVUjuKy2zCVgcuKLi
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Sources:
https://arxiv.org/pdf/1412.7584.pdf
https://people.eecs.berkeley.edu/~stephentu/writeups/6885-lec20-b.pdf
https://towardsdatascience.com/understanding-differential-privacy-85ce191e198a
https://en.wikipedia.org/wiki/Differential_privacy
https://arxiv.org/abs/1610.05492
https://dl.acm.org/doi/abs/10.1145/3298981?casa_token=4kytV-24vgUAAAAA:BXHZafaHQW1A7_VYHsxnKmXmA0DHC7XrU4WzCjGj4l-hNow1-Pu1bw4Ste97yw5gZ9jjOwITczWHbQ
https://arxiv.org/abs/1712.07557
https://arxiv.org/abs/1611.04482
https://arxiv.org/abs/1811.12470
https://arxiv.org/abs/1908.07873
https://www.sciencedirect.com/science/article/abs/pii/S138650561830008X
https://research.google/pubs/pub45648/
https://towardsdatascience.com/the-new-dawn-of-ai-federated-learning-8ccd9ed7fc3a
https://federated.withgoogle.com/
https://towardsdatascience.com/the-new-dawn-of-ai-federated-learning-8ccd9ed7fc3a
https://en.wikipedia.org/wiki/Federated_learning
https://ai.googleblog.com/2017/04/federated-learning-collaborative.html
