PyData 2022 July

Welcome to the July Pydata Berlin edition!!

For everybody to feel safer, we recommend you to test yourself against COVID19 before coming to the event. A self test or a rapid antigen test would suffice. And please refrain from coming to the event if you feel unwell.

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Talks:
Jay Alammar
Large Language Models for Real-World Applications - A Gentle Intro
Machine language understanding and generation has been undergoing rapid improvements due to recent breakthroughs in machine learning (e.g. large language models like GPT and BERT). And while big tech and NLP engineers were quick to capitalize on these models, the broader developer community lags in adopting these models and realizing their potential in their business domains.

This talk provides a gentle and highly visual overview of some of the main intuitions and real-world applications of large language models. It assumes no prior knowledge of language processing and aims to bring attendees up to date with the fundamental intuitions and applications of large language models.

Bio
Jay is a partner machine learning engineer at Cohere. Through his popular machine learning blog, Jay has helped millions of engineers and data scientists visually understand machine learning tools and concepts from the basic (ending up in NumPy, pandas docs) to the cutting-edge (The Illustrated Transformer, BERT, GPT-3).

Break

Franziska Boenisch
Privacy in Machine Learning and Federated Learning
Machine learning (ML) applications are widely deployed and operate on our sensitive data. Unfortunately, our private information about that data can leak from ML pipelines and trained models. Therefore, the topic of privacy-preserving ML is of high importance. In this talk, I will first introduce the state-of-the-art privacy attacks against ML models, then give an overview on privacy risks and and and leakage. Finally, I will present my most recent work on highly efficient data extraction attacks in federate learning which highlight the importance of adequately protecting trained ML models and their training processes.

Bio
Franziska Boenisch is a research associate at the Fraunhofer institute for Applied and Integrated Security and a final year PhD candidate in the Computer Science Department at Freie University Berlin. Her research focuses on trustworthy machine learning and privacy. She received a Fraunhofer grant for outstanding female early career researchers and the German Industrial Research Foundation prize for her applied research. Prior to her PhD, she did her Master’s in computer science at Freie University Berlin and Technical University Eindhoven.

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NumFOCUS Code of Conduct
THE SHORT VERSION

Be kind to others. Do not insult or put down others. Behave professionally. Remember that harassment and sexist, racist, or exclusionary jokes are not appropriate for NumFOCUS.
All communication should be appropriate for a professional audience including people of many different backgrounds. Sexual language and imagery is not appropriate.

NumFOCUS is dedicated to providing a harassment-free community for everyone, regardless of gender, sexual orientation, gender identity, and expression, disability, physical appearance, body size, race, or religion. We do not tolerate harassment of community members in any form.
Thank you for helping make this a welcoming, friendly community for all.

If you haven't yet, please read the detailed version here: https://numfocus.org/code-of-conduct

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SPONSORS:

BackMarket
Founded in 2014 in France, Back Market is the world's first online marketplace dedicated exclusively to second-hand devices to allow the consumer to enjoy a shopping experience with the associated advantages one has when buying new, but at a cheaper price.
- Website: https://www.backmarket.com/
- Jobs: https://jobs.backmarket.com/
- LinkedIn: https://www.linkedin.com/company/back-market/

Jina AI
Jina is a deep learning-powered search framework for building cross-/multi-modal search systems (e.g., text, images, video, audio) on the cloud.
- Website: https://jina.ai
- Github: https://github.com/jina-ai/jina
- Twitter: https://twitter.com/JinaAI_
- LinkedIn: https://www.linkedin.com/company/jinaai/mycompany/

Ahoy Berlin coworking space
https://www.ahoyberlin.com/
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How to find us:
The meetup happens at Ahoy coworking space (https://www.ahoyberlin.com) and you can find us on 2.OG on the main event space.