PyLadies Berlin are excited to bring you this open source workshop dedicated to setting up your scikit-learn or fairlearn development environment.

scikit-learn is a popular machine learning library and is widely adopted in industry as well as academia.

Fairlearn is a community-driven project to help data scientists improve fairness of AI systems.

This is a warm-up session for the upcoming workshop, but it is open to anyone who would like to get guidance, even if you won’t attend the workshop. No prior contributing experience required!

By setting up your development environment in advance, you can use the in-person workshop time for finding an issue to work on, and working on a contribution.

• Format for the session: First 10 minutes : welcome and introduction The rest : "office hours" during which you can ask questions and where you'll be supported with setting up a development environment.

• Preparation work for scikit-learn To get the most out of the session, it's encouraged that you check out the Developer's Guide of scikit-learn and follow steps 1 to 7 under the section "How to contribute": https://scikit-learn.org/dev/developers/contributing.html#how-to-contribute. You will also find a lot of useful additional information on this page, for example video resources: https://scikit-learn.org/dev/developers/contributing.html#video-resources. Please be aware that it could take longer to set up a development environment on ​​a computer running a Windows operating system compared to MacOS or Unix. If you are using Windows, it is recommended to install Windows Subsystem for Linux. You can find instructions on the installation process for example by following the steps described here: https://learn.microsoft.com/en-us/windows/wsl/install. Please note that you should be using WSL 2, and here's how you can upgrade to this version if you have WSL 1: https://learn.microsoft.com/en-us/windows/wsl/install#upgrade-version-from-wsl-1-to-wsl-2

• Preparation work for Fairlearn You don't need to do any preparation work for Fairlearn for this session, instructions will be given during this event. However, it is recommended that you have a look at the Fairlearn Contributor Guide here: https://fairlearn.org/v0.12/contributor_guide/index.html

• How to join We'll be using Discord for this event. Please follow the steps below: 1. Join the scikit-learn Discord server: https://discord.gg/aBgkfXBtWZ 2. Join the #help-desk-voice channel. This is the channel where we'll be hosting this workshop.

• Audience level Everyone is welcome to attend this session! If you've never contributed to open source software before, then you will learn how to, and if you have experience contributing, then you can either help mentor other attendees or you can work on more challenging contributions. It is useful to have some scikit-learn, git, and python experience.

• Facilitators The session will be lead by Maren Westermann (PyLadies Berlin, scikit-learn team member), Tamara Atanasoska (scikit-learn contributor, Fairlearn maintainer), Stefanie Senger (scikit-learn team member), Adrin Jalali (scikit-learn and Fairlearn maintainer) and Guillaume Lemaitre (scikit-learn maintainer).

• By attending our event, you agree to the PyLadies Code of Conduct: https://www.pyladies.com/CodeOfConduct/

❓ Can men attend ❓ Everyone is welcome. If you identify as someone well-represented in open source and in tech, please be mindful of the space and privileges you have, and use it to support others.

• Contact Interested in speaking at one of our events? Have a good idea for a Meetup? Get in touch with us at [email protected] Find us on the PyLadies Global workspace: 1. https://slackin.pyladies.com enter your email address. 2. Accept the email invitation 3. Go to workspace https://pyladies.slack.com 4. Join channel #city-berlin\, #germany\, #jobs-europe

Dear PyLadies 💚🐍

Our next on-site event is coming on the 27th of November featuring 𓆙 Adrin Jalali from Probabl and Celia Kherfallah from Zama and continuing with ⚡ lightning talks where you can take 3 mins to talk about anything Python or tech related (more below)

🌟Agenda (preliminary)

18h30 - 18h45 Come and take your seat

18h45 - 19h00 Welcome by PyLadies Paris and GitGuardian

19h00 - 19h30 Let’s exploit pickle, and `skops` to the rescue! by Adrin Jalali from Probabl.

19h30 - 20h00 Privacy-Preserving Machine Learning With Fully Homomorphic Encryption (FHE) by Celia Kherfallah from Zama

20h00 - 20h20 Lightning talks

20h20 - 22h00 Pizza & networking

🌟 Adrin Jalali from Probabl Talk Title: Let’s exploit pickle, and `skops` to the rescue!

Abstract: Pickle files can be evil and simply loading them can run arbitrary code on your system. This talk presents why that is, and we show in simple ways how you can create such an exploit. It would give you a good basis to understand pickle vulnerabilities. This talk also gives you the resources to find more about these exploits.

We then talk about how `skops` [1] is tackling the issue for scikit-learn/statistical ML models. We go through some lower level pickle related machinery, and go in detail how the new format works. The new format does not only solve the issue for scikit-learn models, but also for most third party estimators which are in the same ecosystem.

In terms of usage, you can simply change two import statements and use the new format almost as a drop in replacement.

- [1] https://skops.readthedocs.io/en/stable/persistence.html

About Adrin: Adrin, a cofounder at probabl.ai, works on a few open source projects including skops which tackles some of the MLOps challenges related to scikit-learn models. He has a PhD in Bioinformatics, has worked as a consultant, and in an algorithmic privacy and fairness team. He's also a core developer of scikit-learn and fairlearn.

🌟 Celia Kherfallah from Zama Talk Title: Privacy-Preserving Machine Learning With Fully Homomorphic Encryption (FHE)

Abstract: We live in an era where the amount of online data has reached hundreds of zettabytes, and cloud services are evolving at an unprecedented rate. Despite tighter regulations, the risk of personal data misuse remains a major concern. At Zama, we believe that responsibility for this issue doesn’t rest with Internet users, but with developers. It is their duty to ensure the protection and security of the data they process.

In this talk, we'll raise awareness among developers about the importance of data privacy, thanks to Fully Homomorphic Encryption (FHE). We'll also introduce Zama's Concrete ML library, which provides the necessary tools (built using FHE) for training models, performing inference on encrypted data, and deploying these solutions, which will enable developers to integrate strong privacy protections without requiring any specific knowledge in cryptography.

About Celia: Celia, Machine Learning Researcher at Zama, has contributed to the development of the Concrete ML library and to the democratization of Fully Homomorphic Encryption (FHE) in the field of Machine Learning.

Get ready for lightning talks: Many of you told us that you would like to give a talk, but your project is not mature enough. You no longer have to worry about it. Come and practice your public speaking during the 3 minutes time-slot. Some ideas on what you can talk about:

• Python library or function you love or which you recently discovered,
• article you've read
• your journey into Python
• conference you have attended

You can decide anytime before the start of lightning talks or you may want to prepare up to one slide (in pdf format) which you can send us the latest on the 11th of March to [email protected]

GitGuardian will be our host and sponsor of the food and the drinks during the networking session after the talks: thank you 💚 and special thanks to Oscar Burns and Antoine Gaillard from GitGuardian for all the support.

Important info

1:❗For safety reasons, the venue's staff will check everyone's identity on site. 📝Please remember to bring an ID with you and register for the event with your real name and family name. Thank you!

2: Please be on time. We can’t guarantee a seat once the meetup has started

# 🔍 FAQ

Q. I'm not female, is it ok for me to attend?

A. Yes, PyLadies Paris events are open to everyone at all levels.

PyLadies Berlin are excited to bring you this open source workshop dedicated to contributing to scikit-learn!

scikit-learn is a popular machine learning library and is widely adopted in industry as well as academia. In this session, you will be guided on how you can make your own contributions to the project, no prior experience in contributing required! Not only will this teach you new skills and boost your CV, you'll also likely get a nice adrenaline rush when your contribution is accepted! If you don’t finish your contribution during the event, we hope you will continue to work on it after the workshop. PyLadies Berlin also offers regular open source hack events where you can continue to meet and work on your contributions together.

• Format for the session: 6:30 - 6:45 pm: Welcome, networking, food and drinks 6:45 - 6:50 pm Community announcements 6:50 - 7:00 pm: Introduction to scikit-learn - what you can contribute and how to contribute from 7:00 pm: "Office hours" during which you'll be mentored for making a contribution to scikit-learn.

**Pre Workshop Session** For attending the event it is required that you have successfully installed the dev version of scikit-learn, have set up a dedicated python environment for the project, and that tests are running successfully. We have a dedicated pre-workshop event scheduled for these tasks which will be happening on 27 July. It is mandatory to sign up for this event if you don't have a working development environment. You can install all requirements yourself by following the instructions on this repository under "1.environment.md" and "2.building.md": https://github.com/scikit-learn-inria-fondation/EuroSciPy22 . You will also find a lot of useful additional information on this page. Note that during the main workshop, we won't have the resources to help you set up your environment.

❓ Can men attend ❓ Everyone is welcome. :) If you identify as someone well-represented in open source and in tech, please be mindful of the space and privileges you have, and use it to support others.

• Audience level Everyone is welcome to attend this session! If you've never contributed to open source software before, then you will learn how to, and if you have experience contributing, then you can either help mentor other attendees or you can work on more challenging contributions. It is useful to have some scikit-learn, git, and python experience.

• Facilitators The session will be lead by Maren Westermann (PyLadies Berlin, scikit-learn contributor experience team), Adrin Jalali (scikit-learn maintainer), and Guillaume Lemaitre (scikit-learn maintainer), Stefanie Senger (scikit-learn intern), and Noa Tamir (PyLadies Berlin, pandas maintainer)

• Host This event is being sponsored by DB Systel GmbH Food and drinks will be available by our hosts 🥳

• By attending our event, you agree to the PyLadies Code of Conduct: https://www.pyladies.com/CodeOfConduct/

• Contact Interested in speaking at one of our events? Have a good idea for a Meetup? Get in touch with us at [email protected] Find us on the PyLadies Global workspace: 1. https://slackin.pyladies.com enter your email address. 2. Accept the email invitation 3. Go to workspace https://pyladies.slack.com 4. Join channel #city-berlin\, #germany\, #jobs-europe

PyLadies Berlin are excited to bring you this open source workshop dedicated to setting up your scikit-learn development environment.

scikit-learn is a popular machine learning library and is widely adopted in industry as well as academia. This is a warm-up session for the upcoming workshop, but it is open to anyone who would like to get guidance, even if you won’t attend the workshop. No prior contributing experience required!

By setting up your development environment in advance, you can use the in-person workshop time for finding an issue to work on, and working on a contribution.

In addition, PyLadies Berlin offers regular open source hack events where you can continue to meet and work on your contributions together.

• Format for the session: First 10 minutes : welcome and introduction The rest : "office hours" during which you can ask questions and where you'll be supported with setting up a development environment.

• Preparation work To get the most out of the session, it's encouraged that you check out the following repository and follow the instructions under "1.environment.md" and "2.building.md": https://github.com/scikit-learn-inria-fondation/EuroSciPy22 . You will also find a lot of useful additional information on this page. Please be aware that it could take longer to set up a development environment on ​​a computer running a Windows operating system compared to MacOS or Unix. If you are using Windows, it is recommended to install Windows Subsystem for Linux. You can find instructions on the installation process for example by following the steps described here: https://learn.microsoft.com/en-us/windows/wsl/install Please note that you should be using WSL 2, and here's how you can upgrade to this version if you have WSL 1: https://learn.microsoft.com/en-us/windows/wsl/install#upgrade-version-from-wsl-1-to-wsl-2

• How to join We'll be using Discord for this event. Please follow the steps below: 1. Join the scikit-learn Discord server: https://discord.com/invite/4GbqW7vpbS 2. Join the #help-desk-voice channel. This is the channel where we'll be hosting this workshop.

• Audience level Everyone is welcome to attend this session! If you've never contributed to open source software before, then you will learn how to, and if you have experience contributing, then you can either help mentor other attendees or you can work on more challenging contributions. It is useful to have some scikit-learn, git, and python experience.

• Facilitators The session will be led by Maren Westermann (PyLadies Berlin, scikit-learn contributor experience team), Adrin Jalali (scikit-learn maintainer), and Guillaume Lemaitre (scikit-learn maintainer), and Stefanie Senger (scikit-learn intern).

• By attending our event, you agree to the PyLadies Code of Conduct: https://www.pyladies.com/CodeOfConduct/

❓ Can men attend ❓ Everyone is welcome. :) If you identify as someone well-represented in open source and in tech, please be mindful of the space and privileges you have, and use it to support others.

• Contact Interested in speaking at one of our events? Have a good idea for a Meetup? Get in touch with us at [email protected] Find us on the PyLadies Global workspace: 1. https://slackin.pyladies.com enter your email address. 2. Accept the email invitation 3. Go to workspace https://pyladies.slack.com 4. Join channel #city-berlin\, #germany\, #jobs-europe