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PPML: Machine Learning on Data you cannot see


Speaker:: Valerio Maggio

Track: PyData: Data Handling
What if I tell you that you can run a complete ML pipeline on private data, without any anonymisation, nor even accessing the data in the first place? 🧐 And what If I also tell you that you can do that with no disruption to your existing pipeline, nor affecting the overall model performance? 😱 Well, that wouldn't be entirely true 😇 but in this workshop we'll explore the great potential **privacy-preserving machine learning** methods have to run _machine learning experiments on data you cannot see_. In the first part, we will first explore examples of exploits and vulnerabilities of Deep Learning models trained on anonymised data, whilst in the second part we will go much deeper into PPML methods, training DL on encrypted data, and more. You'll just have to be familiar with PyTorch, and DL basics to attend this workshop!

Recorded at the PyConDE & PyData Berlin 2022 conference, April 11-13 2022.
More details at the conference page:


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