Conferences / PyData
PyCon DE & PyData Berlin 2023
Apr 17–19, 2023 · bcc Berlin Congress Center, Berlin, Germany
- Conference
- PyData Data science & ML
- Dates
- Apr 17, 2023 – Apr 19, 2023
- Venue
- bcc Berlin Congress Center
- Place
- Berlin, Germany
- Format
- Hybrid
- Status
- Past
- Attendance
- —
- Website
- 2023.pycon.de
- Recorded
- 39 sponsors · 138 speaker appearances
- Notes
- Joint conference branded 'PyCon DE & PyData Berlin' (PyCon DE plus PyData Berlin), organised by the Python Software Verband e.V. (PySV) with NumFOCUS/PyData; recorded under the berlin suffix. Hybrid (in-person plus online tickets). Late-bird Individual price is 490 EUR in the FAQ but 475 EUR in the Jan 2023 tickets blog post; FAQ value used. Speakers: full pretalx schedule; affiliations from the 'Affiliation:' field on 2023.pycon.de session pages.
Ticket prices
| Ticket | Price | Valid until | Notes | Source |
|---|---|---|---|---|
| Online Student (regular) | €50 | — | 2023.pycon.de | |
| Online Individual (regular) | €90 | — | 2023.pycon.de | |
| Online Business (regular) | €190 | — | 2023.pycon.de | |
| In-person Student (regular) | €225 | — | 2023.pycon.de | |
| In-person Student (late bird) | €300 | — | 2023.pycon.de | |
| In-person Individual (regular) | €375 | — | 2023.pycon.de | |
| In-person Individual (late bird) | €490 | — | 2023.pycon.de | |
| In-person Business (regular) | €590 | — | Regular price for the first 800 tickets | 2023.pycon.de |
| In-person Business (late bird) | €800 | — | 2023.pycon.de |
Sponsors 39
Title / headline 4
- Deutsche Post DHL Group · Diamond
- JetBrains · Diamond
- Kleinanzeigen · Diamond
- Snowflake · Diamond
Silver 7
Community 4
- PyData Berlin · Community Partners
- PyData Frankfurt · Community Partners
- PyData Südwest · Community Partners
- PyLadies · Community Partners
Other 4
- Django Software Foundation · Diversity & Financial Aid Sponsors
- EuroPython Society · Diversity & Financial Aid Sponsors
- inovex · Diversity & Financial Aid Sponsors
- Python Software Foundation · Diversity & Financial Aid Sponsors
Speakers and talks 138
| Speaker | Company | Role | Talk | Links |
|---|---|---|---|---|
| Carsten Binnig | — | Keynote | Keynote - Towards Learned Database Systems | — |
| Miroslav Šedivý | — | Keynote | Keynote - Lorem ipsum dolor sit amet | — |
| Noa Tamir | neue fische | Keynote | Keynote - How Are We Managing? Data Teams Management IRL | — |
| Susan Shu Chang | Quill Game Studios | Keynote | Keynote - A journey through 4 industries with Python: Python's versatile problem-solving toolkit | — |
| AbdealiLoKo | Corridor Platforms | Talk | Monorepos with Python | — |
| Alejandro Saucedo | The Institute for Ethical AI & Machine Learning | Talk | The State of Production Machine Learning in 2023 | — |
| Aleksander Molak | CausalPython.io / Lespire.io | Tutorial | The Battle of Giants: Causality vs NLP => From Theory to Practice | — |
| Alexander CS Hendorf | KÖNIGSWEG | Talk | 5 Things about fastAPI I wish we had known beforehand | — |
| Alexander Vosseler | Allianz | Talk | BHAD: Explainable unsupervised anomaly detection using Bayesian histograms | — |
| Alicia Bargar | — | Sponsor | How to build observability into a ML Platform | — |
| Alina Bickel | scieneers | Talk | “Who is an NLP expert?” - Lessons Learned from building an in-house QA-system | — |
| Amit Verma | Flixbus | Sponsor | Dynamic pricing at Flix | — |
| Andreas Leed | Oxford Global Projects | Talk | Accelerating Public Consultations with Large Language Models: A Case Study from the UK Planning Inspectorate | — |
| Anna Achenbach | — | Sponsor | Delivering AI at Scale | — |
| Anna-Lena Popkes | inovex | Talk | An unbiased evaluation of environment management and packaging tools | — |
| Antoine Toubhans | Sicara | Talk | Advanced Visual Search Engine with Self-Supervised Learning (SSL) Representations and Milvus | — |
| Antonia Scherz | PD-Berater der öffentlichen Hand | Talk | Unlocking Information - Creating Synthetic Data for Open Access. | — |
| Antonio Cuni | Anaconda | Talk | The CPU in your browser: WebAssembly demystified | — |
| Arnault Chazareix | — | Talk | Visualizing your computer vision data is not a luxury, it's a necessity: without it, your models are blind and so do you. | — |
| Artem Kislovskiy | — | Talk | The bumps in the road: A retrospective on my data visualisation mistakes | — |
| Asher Sterkin | BlackSwan Technologies | Talk | Cloud Infrastructure From Python Code: How Far Could We Go? | — |
| Avanindra Kumar Pandeya | HelloFresh | Talk | FastAPI and Celery: Building Reliable Web Applications with TDD | — |
| Bruno Vollmer | biped | Talk | BLE and Python: How to build a simple BLE project on Linux with Python | — |
| Caner Turkmen | Amazon Web Services | Talk | AutoGluon: AutoML for Tabular, Multimodal and Time Series Data | — |
| Cheuk Ting Ho | Anaconda | Talk | Driving down the Memray lane - Profiling your data science work | — |
| Christian Bourjau | — | Sponsor | Have your cake and eat it too: Rapid model development and stable, high-performance deployments | — |
| Christopher Prohm | — | Talk | Pragmatic ways of using Rust in your data project | — |
| Clara Hoffmann | RC Trust - TU Dortmund | Talk | Honey, I broke the PyTorch model >.< - Debugging custom PyTorch models in a structured manner | — |
| Cole Bailey | Delivery Hero | Sponsor | Cooking up a ML Platform: Growing pains and lessons learned | — |
| Corrie Bartelheimer | OTA Insight | Talk | Code Cleanup: A Data Scientist's Guide to Sparkling Code | — |
| Damian Bogunowicz | Neural Magic | Talk | Why GPU Clusters Don't Need to Go Brrr? Leverage Compound Sparsity to Achieve the Fastest Inference Performance on CPUs | — |
| Daryna Dementieva | Technical University of Munich | Talk | Methods for Text Style Transfer: Text Detoxification Case | — |
| David Andersson | Canonical | Talk | Giving and Receiving Great Feedback through PRs | — |
| Dishant Sethi | Velotio Technologies | Talk | Introduction to Async programming | — |
| Dr. Lisa Andreevna Chalaguine | — | Tutorial | How to teach NLP to a newbie & get them started on their first project | — |
| Dr. Thomas Wiecki | PyMC Labs | Talk | Bayesian Marketing Science: Solving Marketing's 3 Biggest Problems | — |
| Ellen König | — | Sponsor | A concrete guide to time-series databases with Python | — |
| Emeli Dral | Evidently AI | Talk | Staying Alert: How to Implement Continuous Testing for Machine Learning Models | — |
| Erin Mikail Staples | Heartex | Talk | Improving Machine Learning from Human Feedback | — |
| Etzik Bega | BSTLabs | Talk | Cloud Infrastructure From Python Code: How Far Could We Go? | — |
| Felix Wick | Blue Yonder | Sponsor | Exploring the Power of Cyclic Boosting: A Pure-Python, Explainable, and Efficient ML Method | — |
| Florian Wilhelm | inovex | Talk | WALD: A Modern & Sustainable Analytics Stack | Slides |
| Gregor Riegler | — | Tutorial | Data Kata: Ensemble programming with Pydantic #1 | — |
| Gregor Riegler | — | Tutorial | Data Kata: Ensemble programming with Pydantic #2 | — |
| Guido Imperiale | Coiled | Talk | Data-driven design for the Dask scheduler | — |
| Guillem Borrell | BCG | Tutorial | Most of you don't need Spark. Large-scale data management on a budget with Python | — |
| Gunar Maiwald | idealo internet GmbH | Talk | Machine Learning Lifecycle for NLP Classification in E-Commerce | — |
| Heiner Tholen | alcemy GmbH | Sponsor | A concrete guide to time-series databases with Python | — |
| Hendrik Makait | Coiled | Talk | Observability for Distributed Computing with Dask | — |
| Ines Montani | Explosion | Talk | Incorporating GPT-3 into practical NLP workflows | — |
| Inga Janczuk | OLX Group | Talk | When A/B testing isn’t an option: an introduction to quasi-experimental methods | — |
| Jakub Bachurski | QuantCo | Sponsor | Have your cake and eat it too: Rapid model development and stable, high-performance deployments | — |
| Jens Agerberg | KTH Royal Institute of Technology | Talk | Teaching Neural Networks a Sense of Geometry | — |
| Jens Nie | ROSEN Creation GmbH | Talk | Accelerating Python Code | — |
| Jeremy TULOUP, QuantStack | — | Talk | The future of the Jupyter Notebook interface | — |
| Jeremy TULOUP, QuantStack | — | Tutorial | Create interactive Jupyter websites with JupyterLite | — |
| John Sandall | Coefficient | Talk | Postmodern Architecture: The Python Powered Modern Data Stack | — |
| Jonathan Brandt | sovanta AG | Talk | Bringing NLP to Production (an end to end story about some multi-language NLP services) | — |
| Joris Van den Bossche | Voltron Data | Talk | Pandas 2.0 and beyond | — |
| Joris Van den Bossche | Voltron Data | Talk | Apache Arrow: connecting and accelerating dataframe libraries across the PyData ecosystem | — |
| Jürgen Gmach | Canonical | Talk | Behind the Scenes of tox: The Journey of Rewriting a Python Tool with more than 10 Million Monthly Downloads | — |
| Katrin Reininger | I-WUNDER GmbH | Talk | How Chatbots work – We need to talk! | — |
| KIlian Kluge | Inlinity | Talk | Grokking Anchors: Uncovering What a Machine-Learning Model Relies On | — |
| Kolja Maier | — | Talk | Specifying behavior with Protocols, Typeclasses or Traits. Who wears it better (Python, Scala 3, Rust)? | — |
| Larissa Haas | sovanta AG | Talk | Bringing NLP to Production (an end to end story about some multi-language NLP services) | — |
| Lea Petters | inovex | Talk | What could possibly go wrong? - An incomplete guide on how to prevent, detect & mitigate biases in data products | Slides |
| Leonard Püttmann | Kern AI | Tutorial | Contributing to an open-source content library for NLP | — |
| Lev Konstantinovskiy | unemployed | Tutorial | Data Kata: Ensemble programming with Pydantic #1 | — |
| Lev Konstantinovskiy | unemployed | Talk | Prompt Engineering 101: Beginner intro to LangChain, the shovel of our ChatGPT gold rush." | — |
| Lev Konstantinovskiy | unemployed | Tutorial | Data Kata: Ensemble programming with Pydantic #2 | — |
| Luis Fernando Alvarez | Stack Builders | Talk | How to connect your application to the world (and avoid sleepless nights) | — |
| Marcus Tedesco | Briink Intelligence GmbH | Talk | Neo4j graph databases for climate policy | — |
| Maren Westermann | DB Systel GmbH | Talk | How to increase diversity in open source communities | — |
| Marianne Stecklina | Omni | Talk | Using transformers – a drama in 512 tokens | — |
| Martin Christen | Universitry of Applied Sciences and Arts Northwestern Switzerland. Institute Geomatics | Tutorial | Geospatial Data Processing with Python: A Comprehensive Tutorial | — |
| Martin Grund | Databricks | Sponsor | Use Spark from anywhere: A Spark client in Python powered by Spark Connect | — |
| Martin Wistuba | Amazon Web Services | Talk | Hyperparameter optimization for the impatient | — |
| Mathis Lucka | deepset | Talk | Building a Personal Assistant With GPT and Haystack: How to Feed Facts to Large Language Models and Reduce Hallucination. | — |
| Matthias Fey | Kumo | Tutorial | Practical Session: Learning on Heterogeneous Graphs with PyG | — |
| Max Kahan | Vonage | Talk | Fear the mutants. Love the mutants. | — |
| Maxim Danilov | wP soft | Talk | What are you yield from? | — |
| Michael Gorkow | Snowflake | Sponsor | Large Scale Feature Engineering and Datascience with Python & Snowflake | — |
| Michele Dallachiesa | Signal Forge | Talk | Accelerating Public Consultations with Large Language Models: A Case Study from the UK Planning Inspectorate | — |
| Mike Müller | Python Academy | Tutorial | Aspect-oriented Programming - Diving deep into Decorators | — |
| Nandana Sreeraj | Censius | Talk | Thou Shall Judge But With Fairness: Methods to Ensure an Unbiased Model | — |
| Nico Kreiling | scieneers | Talk | Raised by Pandas, striving for more: An opinionated introduction to Polars | — |
| Nico Kreiling | scieneers | Talk | “Who is an NLP expert?” - Lessons Learned from building an in-house QA-system | — |
| Nikolai | Heartex | Talk | Improving Machine Learning from Human Feedback | — |
| Nitsan Avni | — | Tutorial | Data Kata: Ensemble programming with Pydantic #1 | — |
| Nitsan Avni | — | Tutorial | Data Kata: Ensemble programming with Pydantic #2 | — |
| Noa Tamir | neue fische | Tutorial | Let's contribute to pandas (3 hours) #2 | — |
| Noa Tamir | neue fische | Tutorial | Let's contribute to pandas (3 hours) #1 | — |
| Noé Achache | Sicara | Talk | Advanced Visual Search Engine with Self-Supervised Learning (SSL) Representations and Milvus | — |
| Oleksandr Shchur | Amazon Web Services | Talk | AutoGluon: AutoML for Tabular, Multimodal and Time Series Data | — |
| Paolo Melchiorre | 20tab | Talk | Maps with Django | — |
| Pasha Finkelshteyn | JetBrains | Sponsor | The Spark of Big Data: An Introduction to Apache Spark | — |
| Patrick Blöbaum | Amazon Web Services | Talk | Performing Root Cause Analysis with DoWhy, a Causal Machine-Learning Library | — |
| Patrick Hoefler | Coiled | Tutorial | Let's contribute to pandas (3 hours) #2 | — |
| Patrick Hoefler | Coiled | Tutorial | Let's contribute to pandas (3 hours) #1 | — |
| Patrick Hoefler | Coiled | Talk | Pandas 2.0 and beyond | — |
| Paul Elvers | Datadrivers | Talk | Maximizing Efficiency and Scalability in Open-Source MLOps: A Step-by-Step Approach | — |
| Paula Gonzalez Avalos | — | Tutorial | Workshop on Privilege and Ethics in Data | — |
| Pavel Zwerschke | QuantCo | Talk | Shrinking gigabyte sized scikit-learn models for deployment | — |
| Ramona Bendias | Kumo | Tutorial | Practical Session: Learning on Heterogeneous Graphs with PyG | — |
| Robert Lange | Technical University Berlin | Talk | evosax: JAX-Based Evolution Strategies | — |
| Robin Raymond | Taktile | Talk | Rusty Python: A Case Study | — |
| samsja | Jina AI | Talk | Modern typed python: dive into a mature ecosystem from web dev to machine learning | — |
| Sanket Verma | Zarr | Talk | The Beauty of Zarr | — |
| Sarthika Dhawan | Microsoft | Talk | You've got trust issues, we've got solutions: Differential Privacy | — |
| Severin Schmitt | Deutsche Post DHL Group | Sponsor | Delivering AI at Scale | — |
| Shahriyar Rzayev | Nord Security | Tutorial | Building Hexagonal Python Services | — |
| Simon Pressler | KÖNIGSWEG | Talk | Getting started with JAX | — |
| Stephan Sahm | — | Tutorial | Accelerate Python with Julia | — |
| Suzin You | IDinsight | Talk | Ask-A-Question: an FAQ-answering service for when there's little to no data | — |
| Sven Oehler | Bytefabrik.AI | Talk | Apache StreamPipes for Pythonistas: IIoT data handling made easy! | — |
| Tereza Iofciu | — | Tutorial | Workshop on Privilege and Ethics in Data | — |
| Tereza Iofciu | — | Talk | Rethinking codes of conduct | — |
| Theodore Meynard | GetYourGuide | Talk | Software Design Pattern for Data Science | — |
| Theodore Meynard | GetYourGuide | Talk | MLOps in practice: our journey from batch to real-time inference | — |
| Thomas Bierhance | BettercallPaul | Talk | Polars - make the switch to lightning-fast dataframes | — |
| Thomas Fraunholz | WOGRA AG | Talk | From notebook to pipeline in no time with LineaPy | — |
| Thorsten Kranz | — | Sponsor | Delivering AI at Scale | — |
| Tim Bossenmaier | inovex | Talk | Apache StreamPipes for Pythonistas: IIoT data handling made easy! | — |
| Tim Hoffmann | Carl Zeiss AG | Sponsor | How Python enables future computer chips | — |
| Tobias Senst | idealo internet GmbH | Talk | Machine Learning Lifecycle for NLP Classification in E-Commerce | — |
| Tobias Sterbak | — | Talk | How to baseline in NLP and where to go from there | — |
| Travis Hathaway | Anaconda | Talk | Writing Plugin Friendly Python Applications | — |
| Tvrtko Sternak | airt | Talk | Introducing FastKafka | — |
| Vadim Nelidov | Xebia | Talk | Common issues with Time Series data and how to solve them | — |
| Valerio Maggio | Anaconda | Talk | Actionable Machine Learning in the Browser with PyScript | Slides |
| Vibha Vikram Rao | Briink | Talk | Haystack for climate Q/A | — |
| Victoria Slocum | Explosion | Talk | You are what you read: Building a personal internet front-page with spaCy and Prodigy | — |
| Vikram Waradpande | Columbia University | Talk | You've got trust issues, we've got solutions: Differential Privacy | — |
| Wiktoria Dalach | wiktoriadalach.com | Talk | Great Security Is One Question Away | — |
| Yann Lemonnier | — | Sponsor | Enabling Machine Learning: How to Optimize Infrastructure, Tools and Teams for ML Workflows | — |
| Yasin Tatar | — | Talk | Shrinking gigabyte sized scikit-learn models for deployment | — |
| Yuichiro Tachibana | — | Talk | Streamlit meets WebAssembly - stlite | — |
| Yuqiong Weng | I-WUNDER GmbH | Talk | How Chatbots work – We need to talk! | — |