Apache StreamPipes for Pythonistas: IIoT data handling made easy!
Tim Bossenmaier, Sven Oehler

Data enthusiasts love to play with IIoT data. However, the technical challenges remain high (e.g., connect to devices). @StreamPipes makes this easy by providing a self-service toolbox. In this talk, we introduce a new python module to work with IIoT data in a pythonic way.

Bringing NLP to Production (an end to end story about some multi-language NLP services)
Larissa Haas, Jonathan Brandt

How to bring NLP models to production? Following a use case that runs for over 1 year in 10 different languages, this talk will enable you to ask the right questions before starting to deploy NLP services.

Create interactive Jupyter websites with JupyterLite
Jeremy Tuloup

Do you want to create your own interactive Jupyter website with JupyterLite? Check out this step-by-step tutorial and learn how to configure and customize your website 💡

Delivering AI at Scale
Severin Schmitt, Anna Achenbach, Thorsten Kranz

Unbelievable tricks to integrate AI into a company with 600k colleagues – experts are shocked!” Learn about Deutsche Post DHL Group’s journey towards a Data-Driven company, with Use Cases, technology details and code snippets #yournextcareerstep #ai #datascience #forecasting

Great Security Is One Question Away
Wiktoria Dalach

Security doesn't have to be a nightmare. The 3rd hack will surprise you.

How Chatbots work – We need to talk!
Yuqiong Weng, Katrin Reininger

We need to talk - All about concepts, techniques as well as practical experience with the Rasa framework for building a chatbot

Keynote - How Are We Managing? Data Teams Management IRL
Noa Tamir

The title “Data Scientist” has been in use for 15 years now. We have been attending PyData conferences for over 10 years as well. The hype around data science and AI seems higher than ever before. But How are we managing? Let's talk about Data Science Management IRL.

PyLadies Panel Session. Tech Illusions and the Unbalanced Society: Finding Solutions for a Better Future

PyLadies chapters around the world reflect on their contributions in advocating for gender representation and leadership as well as combating biases and the gender pay gap.

PyLadies Workshop

Know your rights! PyLadies and Berlin Tech Workers Coalition will unveil important details on work contracts and your rights to get you covered in case of layoffs

Rethinking codes of conduct
Tereza Iofciu

Did you know that the Python Software Foundation Code of Conduct is turning 10 years old in 2023? It was voted in as they felt they were “unbalanced and not seeing the true spectrum of the greater community”. Why is that a big thing? Come to my talk and find out!

The future of the Jupyter Notebook interface
Jeremy Tuloup

Jupyter Notebook 7 is the new version of the popular document-oriented notebook interface. It comes packed with a lot of new features, and its future looks bright!

Using transformers – a drama in 512 tokens
Marianne Stecklina

Nearly all pretrained transformers have an annoying limitation: they can only process short input sequences. Watch me rant about it ;-)

What could possibly go wrong? - An incomplete guide on how to prevent, detect & mitigate biases in data products
Lea Petters

Data Ethics: What could possibly go wrong? - An incomplete guide on how to prevent, detect & mitigate biases in data products

When A/B testing isn’t an option: an introduction to quasi-experimental methods
Inga Janczuk

Have you ever wanted to know the causal effect of an action but A/B testing wasn’t an option? Here’s a brief helicopter tour over quasi-experimental methods that can be used instead!

Workshop on Privilege and Ethics in Data
Tereza Iofciu, Paula Gonzalez Avalos

Data-driven Products are built by humans. Humans are intrinsically biased. This bias goes into the products, which amplifies the original bias. In this tutorial, you will learn how to identify your biases and reflect on the consequences of unchecked biases in Data Products.