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@@ -30,15 +30,15 @@ This workshop will be mainly organised in **two parts**. In the first part, we w
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- Model _Inference attack_ with `OPACUS` notebooks: [training](2-mia-differential-privacy/4-MIA-Training-OPACUS.ipynb) | [reconstruction](2-mia-differential-privacy/5-MIA-Reconstruction-OPACUS.ipynb)
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-**Part 2**: Primer on Privacy-Preserving Machine Learning
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- Introduction to Federated Learning [notebook](./3-federated-learning/1%20Intro%20to%20Federated%20Learning.ipynb)
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- DL training on (Homomorphically) Encrypted Data [notebook](./3-federated-learning/2%20Homomorphic%20Encryption.ipynb)
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- OpenMined and PrivateAI series [notebook](./3-federated-learning/3%20OpenMined%20Private%20AI%20Series.ipynb)
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- Introduction to Federated Learning [notebook](./3-federated-learning/1-Intro-Federated-Learning.ipynb)
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- DL training on (Homomorphically) Encrypted Data [notebook](./3-federated-learning/2-Homomorphic-Encryption.ipynb)
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- OpenMined and PrivateAI series [notebook](./3-federated-learning/3-OpenMined-private-AI-series.ipynb)
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- Introduction to Remote Data Science [notebooks](./3-federated-learning/duet_iris_classifier/)
Clone the current repository, in order to get the course materials. To do so, once connected to your remote machine (via `SSH`), execute the following instructions:
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Clone the current repository by running the following instructions:
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```bash
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cd$HOME# This will make sure you'll be in your HOME folder
Well done! Now you should do be in the right location. Bear with me another few seconds, following instructions reported below 🙏
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Well done! Now you should do be in the right location.
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Bear with me for another few seconds, following instructions reported below 🙏
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### Set up your Environment
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There are indeed two (possibly _three_) methods that you could use to execute the code in the notebooks.
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The **recommended** method is to setup a new `ppml` Python environment on your local machine.
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Please refer to the [`setup.md`](./setup.md) document for a step-by-step guide on how to setup the environment, and check that all is working.
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Please refer to the [`setup.md`](./setup.md) document for a step-by-step guide on how to set up the environment, and to check that all is working.
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**Alternartively** you could rely on services such as [MyBinder](https://mybinder.org) or [Google Colab](https://colab.research.google.com) to run the notebooks interactively, and without needing to setup your Python environment locally.
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**Alternartively** you could rely on services such as [MyBinder](https://mybinder.org) or [Google Colab](https://colab.research.google.com) to run the notebooks interactively, and without needing to install anything.
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[](https://mybinder.org/v2/gh/leriomaggio/ppml-tutorial/HEAD) | [](https://colab.research.google.com/github/leriomaggio/ppml-tutorial/blob/main/index.ipynb)
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However, these alternative solutions come with some **caveats and workarounds** that should be considered:
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1. MyBinder does not support connection to remote hosts on (not-allowed ports). Therefore, the entire Section 3 on Federated Learning and `syft` does not work.
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2. To use Google Colab it is necessary to have a **Google Account**. Plus, the environment cannot be setup automatically (notebooks contain additional instructions to do so, in case)
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1. MyBinder does not support connection to remote hosts on (not-allowed) network ports. This means that all the examples in Sec. 3 running `syft` and `duet` will **never** work.
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- I would recommend running those notebooks in `Colab` in case.
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2. To use Google Colab it is necessary to have a **Google Account**. Plus, the environment cannot be setup automatically so sometimes additional deps and packages should be installed first
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- On this note, please consider that notebooks requiring additional dependencies contain instructions to do so, in their preamble section.
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