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👋 Hello data privateers and advanced language models!

🗓️ The 27th Prague PyData meetup is sponsored by Rossum and it will take place at Miton offices. The talks will start at 18:30 and we encourage you to come as soon as 18:00 to enjoy the opportunity to socialise and refresh yourselves (which you can continue doing during the break and after the talks).

🤗 Our main goal is to build the community around Python and data and make it welcoming to people of various skills and experience levels.

⚡ If you are interested in giving a lightning talk (up to 5 minutes to present an idea, tool or results related at least to some degree to Python and/or data), please contact us before or during the event.

📢 Anonymization: Why is it so hard? Katharine Jarmul In this talk, we'll look at the problem of anonymizing data and pick apart several common mistakes people make when attempting to remove or modify sensitive data in order to anonymize it. We'll review basic approaches like pseudonymization and redaction, and then look at more advanced approaches like k-anonymization/aggregation and differential privacy. Expect to think a bit like a hacker and a data scientist to see if you can imagine ways to defeat these approaches, and explore how intertwined information theory is to privacy work.

📢 LLMs, the do-it-yourself edition Štěpán Procházka How Rossum researched, trained and deployed their very own T-LLM to process millions of documents a month. #huggingface #pytorch-lightning #nvidia-triton #pgvector #vllm https://rossum.ai/blog/rossum-aurora/

The venue will open at 6.00pm but the intro won't take place sooner than at 6:30pm. There will be refreshments available, 🤗 sponsors!

Please, RSVP here. See you soon, PyData Prague team

The PyData Paris Conference will take place at the Cité des Sciences on Sep 25-26 2024.

📢 Tickets are for sale at https://pydata.org/paris2024.

Hosted by QuantStack and NumFOCUS, this event promises to bring together open-source maintainers and enthusiasts, as well as experts from across the globe, all united by their passion for open-source technologies.

PyData Paris 2024 is a celebration of the thriving Parisian open-source scientific computing and AI/ML community, showcasing the blossoming ecosystem that includes key players such as Hugging Face and Mistral AI, open-source projects like scikit-learn and Jupyter, as well as open-source software corporations like QuantStack and :probabl.

Our conference is honored to feature an impressive lineup of keynote speakers who will share their invaluable insights:

• Arthur Mensch, co-founder and CEO of Mistral AI
• Katharine Jarmul, privacy activist, author, and co-founder of PyLadies
• Olivier Grisel, engineer at :probabl. and developer of scikit-learn
• Merve Noyan, machine learning advocate engineer at Hugging Face

📢 Tickets are for sale at https://pydata.org/paris2024.

DataScience and AI: in person in Kaiserslautern and live on PyData.TV on YouTube

Agenda18:00 Doors open18:30 Welcome18:45 Create dashboards easily with Streamlit – Patrick Holzer19:15 Break: Networking with snacks and beverages20:15 Machine Learning Memorization: Why does it happen? Let's find out!20:40 - Katharine Jarmul20:45 Lightning Talks21:00 Networking with snacks and beverages21:30 End

---Talk #1Create dashboards easily with Streamlit – Patrick Holzer

This talk introduces Streamlit, an easy-to-use yet versatile Python package for creating interactive dashboards. The basics and functionality as well as various elements of Streamlit will be presented. Best practices, use cases and deployment in the Community Cloud will also be discussed.

Patrick Holzer is a mathematical researcher working in the fields of machine learning and quantum computing with a strong enthusiasm for Python. He has been a Streamlit user since the early days of this framework.

Talk #2Machine Learning Memorization: Why does it happen? Let's find out! - Katharine Jarmul -- Details of the talk will be announced soon --

Katharine Jarmul is author of the recent O'Reilly book Practical Data Privacy (https://www.oreilly.com/library/view/practical-data-privacy/9781098129453/). Previously, she has held numerous roles at large companies and startups in the US and Germany, implementing data processing and machine learning systems with a focus on reliability, testability, privacy and security.She is a passionate and internationally recognized data scientist, programmer, and lecturer. Katharine is also a frequent keynote speaker at international software and AI conferences.---

Lightning TalksJoin us by contributing a five-minute lightning talk!Fill out this form (https://bit.ly/pydata-sw-talk).

How to sign up for on siteIt's important for us to make this meet up happen in a responsible way. We have limited seats available only.No limits to sign up remotely!

How to join remotelyDue to technical issues we are unfortunately not streaming today.

This event will be in English.

AcknowledgementsAlso a big thank you to our sponsors:

Fraunhofer ITWM (https://www.itwm.fraunhofer.de/), for hosting the meetup. QuantCo (https://www.quantco.com/) for organising. Pioneers Hub (https://pioneershub.de), for organising. NumFOCUS (https://numfocus.org), for promoting open source software. ContactIf you have any questions or suggestions, please feel free to contact us via:

Meetup Want to speak? Submit a talk here (http://bit.ly/43QBJkn). Interested in hosting an event? Here's our Info-Deck (https://bit.ly/pydata-sw-infodeck) & contact to the organisers (https://www.linkedin.com/groups/12851256/)!

Talk Title: "LLM-driven game characters"

Description: We present AI Game, a novel type of role-playing sandbox game that leverages LLM-powered agents to enhance player experience.

Our game features agents with long-term memory and autonomous goal pursuit, enabled by large language models that emulate their personalities, behaviors, thoughts, actions, and dialogues.

In this talk, we will discuss the technical and design aspects of our game.

Speaker/Bio: Marek Rosa Marek Rosa \| CEO & Founder @ GoodAI, https://www.linkedin.com/in/marekrosa1 & https://blog.marekrosa.org/

Marek Rosa is the founder and CEO of GoodAI, a general artificial intelligence R&D company, and Keen Software House, an independent game development studio, started in 2010, and best known for its best-seller Space Engineers (nearing 5 million copies sold).

Marek has been interested in game development and artificial intelligence since childhood. He started his career as a programmer and later transitioned to a leadership role. After the success of Keen Software House titles, Marek was able to fund GoodAI in 2014 with a $10 Million personal investment.

GoodAI's mission is to develop AGI - as fast as possible - to help humanity and understand the universe. One of the commercial stepping stones is the "AI game," which features LLM-driven NPCs grounded in the game world with developing personalities and long-term memory. GoodAI also works on autonomous agents that can self-improve and solve any task that a human can.

Moderator and Host of the event: Radovan Kavický, President & Principal Data Scientist @ GapData Institute; AI & Data Science Evangelist @ AIslovakIA - National platform for AI development in Slovakia

Fun Fact: Marek (Rosa) & Radovan (Kavicky) were also historically first (+so far still the only) Slovaks who were invited as speakers to PyData Berlin (the biggest Data Science and AI conference under PyData within Europe/outside U.S.) as speakers (few years back, more about it here: PyData Slovakia & Bratislava #7: Berlin edition s Katharine Jarmul \| robime.it - https://robime.it/pydata-bratislava-7-berlin-edition-s-katharine-jarmul/)

LinkedIn: https://www.linkedin.com/in/marekrosa1

Registration:

@Meetup.com group's event here (https://www.meetup.com/pydata-slovakia-bratislava/events/300546803/) & @Eventbrite registration here (https://www.eventbrite.com/e/pydata-slovakia-meetup-28-marek-rosa-llm-driven-game-characters-tickets-887006449167). +our event you can find also @Facebook here (https://www.facebook.com/events/3516416348670649) and LinkedIn here (https://www.linkedin.com/events/pydataslovakiameetup-28-marekro7187710143625650176/comments/).

[Disclaimer: If you just mark "going" @Facebook event we can't guarantee your seat]

Language of the event: English

PyData Bratislava [Python Data Enthusiasts and Users, Data Scientists & Statisticians of all levels from Slovakia]

-- PyData is a group for users and developers of data analysis tools to share ideas and learn from each other. We gather to discuss how best to apply Python tools, as well as those using R and Julia, to meet the evolving challenges in data management, processing, analytics, and visualization. PyData is organized by NumFOCUS.org, a 501(c)3 non-profit in the United States.

The PyData ​Code of Conduct​ governs this meetup. To discuss any issues or concerns relating to the code of conduct or the behavior of anyone at a PyData meetup, please contact the organizer or NumFOCUS Executive Director Leah Silen (+1512-222-5449; [email protected]).

Our Facebook group you can find here: https://www.facebook.com/groups/1813599648877946/

Our Twitter account here: https://twitter.com/PyDataBA

Our LinkedIn group here: https://www.linkedin.com/groups/13506080

Organizers: GapData Institute (https://www.gapdata.org/) (GDI) is a nonprofit nonpartisan research institution harnessing power of data & wisdom of economics for public good.

\|\| Data. Think. Change. \|\|

NumFOCUS (http://www.numfocus.org/) is a 501(c)(3) nonprofit that supports and promotes world-class, innovative, open source scientific computing. The mission of NumFOCUS is to promote sustainable high-level programming languages, open code development, and reproducible scientific research.

Katharine Jarmul and I chat about the Biden AI Executive Order. Enjoy!

We talked about:

Katharine's background Katharine's ML privacy startup GDPR, CCPA, and the “opt-in as the default” approach What is data privacy? Finding Katharine's book – Practical Data Privacy The various definitions of data privacy and “user profiles” Privacy engineering and privacy-enhancing technologies Why data privacy is important What is differential privacy? The importance of keeping privacy in mind when designing systems Data privacy on the example of ChatGPT Katharine's resource suggestions for learning about data privacy

Links:

LinkedIn: https://www.linkedin.com/in/katharinejarmul/

Twitter: https://twitter.com/kjam

Free data engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

Katharine Jarmul (Principal data scientist at Thoughtworks and author of Practical Data Privacy (O’Reilly, 2023)) and I chat about all things data privacy. She brings battle-tested experience and unique perspectives in the areas of ML/AI privacy, AI risk, regulation, and much more. I learned a ton, and I hope you do too!

LinkedIn: https://www.linkedin.com/in/katharinejarmul/

Twitter: https://twitter.com/kjam

Probably Private newsletter: https://probablyprivate.com/

If you like this show, give it a 5-star rating on your favorite podcast platform.

Purchase Fundamentals of Data Engineering at your favorite bookseller.

Check out my substack: https://joereis.substack.com/

Take advantage of today's sky-high demand for data engineers. With this in-depth book, current and aspiring engineers will learn powerful real-world best practices for managing data big and small. Contributors from notable companies including Twitter, Google, Stitch Fix, Microsoft, Capital One, and LinkedIn share their experiences and lessons learned for overcoming a variety of specific and often nagging challenges. Edited by Tobias Macey, host of the popular Data Engineering Podcast, this book presents 97 concise and useful tips for cleaning, prepping, wrangling, storing, processing, and ingesting data. Data engineers, data architects, data team managers, data scientists, machine learning engineers, and software engineers will greatly benefit from the wisdom and experience of their peers. Topics include: The Importance of Data Lineage - Julien Le Dem Data Security for Data Engineers - Katharine Jarmul The Two Types of Data Engineering and Data Engineers - Jesse Anderson Six Dimensions for Picking an Analytical Data Warehouse - Gleb Mezhanskiy The End of ETL as We Know It - Paul Singman Building a Career as a Data Engineer - Vijay Kiran Modern Metadata for the Modern Data Stack - Prukalpa Sankar Your Data Tests Failed! Now What? - Sam Bail

Before the COVID-19 crisis, we were already acutely aware of the need for a broader conversation around data privacy: look no further than the Snowden revelations, Cambridge Analytica, the New York Times Privacy Project, the General Data Protection Regulation (GDPR) in Europe, and the California Consumer Privacy Act (CCPA). In the age of COVID-19, these issues are far more acute. We also know that governments and businesses exploit crises to consolidate and rearrange power, claiming that citizens need to give up privacy for the sake of security. But is this tradeoff a false dichotomy? And what type of tools are being developed to help us through this crisis? In this episode, Katharine Jarmul, Head of Product at Cape Privacy, a company building systems to leverage secure, privacy-preserving machine learning and collaborative data science, will discuss all this and more, in conversation with Dr. Hugo Bowne-Anderson, data scientist and educator at DataCamp.Links from the show

FROM THE INTERVIEW

Katharine on TwitterKatharine on LinkedInContact Tracing in the Real World (By Ross Anderson)The Price of the Coronavirus Pandemic (By Nick Paumgarten)Do We Need to Give Up Privacy to Fight the Coronavirus? (By Julia Angwin)Introducing the Principles of Equitable Disaster Response (By Greg Bloom)Cybersecurity During COVID-19 ( By Bruce Schneier)