Schedule
More than 112 sessions await you.
Wednesday, October 09
talks/keynotes
center
Saal 2talks
front
Saal 10talks
front
Saal 6talks
back, middle
Saal 5talks
center
Loungediv
front
Saal 4Tutorial
back
Saal 7Tutorial
back
09:00
10:30
10:50
11:20
Python
11:50
Tin Marković (Kiwi.com)
Refactoring in Python: Design Patterns and Approaches
PyConDE • Business & Start-Ups, Community, Code-Review12:25
13:00
Micropython
14:00
14:35
Christine Spindler (George Robotics Ltd.)
How MicroPython went into space
PyConDE • Microcontrollers15:05
Deployment
15:30
Marianna Diachuk (Women Who Code Kyiv)
Applying deployment oriented mindset for building Machine Learning models
PyData • Data Science, Machine Learning16:05
Yetunde Dada (QuantumBlack)
Production-level data pipelines that make everyone happy using Kedro
PyData • Data Science, DevOps, Machine Learning, Data Engineering16:50
17:00
Mariatta Wijaya (Zapier)
PEP 581 and PEP 588: Migrating CPython's Issue Tracker
PyConDE • Community, Use Cases17:45
18:30
11:20
Performance
11:50
Eran Friedman (CommonSense Robotics)
Boosting simulation performance with Python
PyConDE • Infrastructure, Robotics12:25
Tilman Krokotsch (IAV GmbH)
Hide Code, Minimize Dependencies, Boost Performance - The PyTorch JIT
PyData • Artificial Intelligence, Deep Learning, Data Science, Machine Learning13:00
Prediction
14:00
Alexey Grigorev (OLX)
Fighting fraud: finding duplicates at scale
PyData • Data Science, Infrastructure, Machine Learning, Data Engineering14:35
Vasily Korf (JetBrains)
AI Intentions and Code Completion
PyData • Artificial Intelligence, Code-Review, IDEs/ Jupyter, Python15:05
ML use-case
15:30
Chiin-Rui Tan (Rho Zeta AI), Dare Imam-Lawal (Rho Zeta AI)
Python-Powered OSINT! Modernising Open Source Intelligence for Investigating Disinformation
PyData • Artificial Intelligence, Algorithms, Data Science, Machine Learning, Web, Data Mining / Scraping, Use Cases16:05
Harald Bosch (Novatec Consulting GmbH)
Creating an Interactive ML Conference Showcase
PyData • Artificial Intelligence, Computer Vision, Deep Learning, IDEs/ Jupyter, Machine Learning11:20
Time Series
11:50
Andrea Spichtinger (Syskron GmbH)
Time Series Anomaly Detection for Bottling Machine Maintenance
PyData • Algorithms, Data Science, Machine Learning12:25
Sean Matthews (Deloitte Analytics Institute), Jannes Quer
Time series modelling with probabilistic programming
PyData • Data Science, Statistics13:00
Julia
14:00
Felicia Burtscher (TU Berlin)
CANCELLED: First steps in Julia
PyData • Artificial Intelligence, Algorithms, Deep Learning, Data Science, Networks, Machine Learning, Science14:35
Simon Danisch (Nextjournal)
Julia for Python
PyData • Data Science, Infrastructure, IDEs/ Jupyter, Parallel Programming15:05
Text
15:30
Roman Yurchak
vtext: text processing in Rust with Python bindings
PyData • Natural Language Processing16:05
Sarah Diot-Girard (PeopleDoc)
Privacy-preserving Machine Learning for text processing
PyData • Artificial Intelligence, Data Science, Natural Language Processing, Machine Learning11:20
Deployment
11:50
12:25
Dr. Tania Allard (Microsoft)
Practical DevOps for the busy data scientist
PyData • Algorithms, Big Data, Data Science, DevOps, Machine Learning13:00
NLP
14:00
Mariana Capinel
Where Linguistics meets Natural Language Processing
PyData • Natural Language Processing14:35
Marianne Stecklina (omni:us)
Why you should (not) train your own BERT model for different languages or domains
PyData • Artificial Intelligence, Deep Learning, Data Science, Natural Language Processing, Machine Learning, Science15:05
Storage/Micropython
15:30
Florian Jetter (Blue Yonder - JDA Software)
Kartothek – Table management for cloud object stores powered by Apache Arrow and Dask
PyData • Big Data, Data Engineering16:05
Nicholas Herriot (Samsung Research Istitute - London)
Using Micropython to develop an IoT multimode sensor platform with an Augmented Reality UI
PyConDE • Augmented Reality, Networks, Microcontrollers, Visualisation11:20
Visualization
11:50
Jan-Benedikt Jagusch (Instaffo GmbH)
Visualizing Interactive Graph Networks in Python
PyData • Data Science, IDEs/ Jupyter, Networks, Visualisation, Python12:25
Daniel Ringler (Ancud IT)
How to choose better colors for your data visualizations
PyData • Data Science, Visualisation13:00
Feature Engineering
14:00
Franziska Horn (TU Berlin)
Automated Feature Engineering and Selection in Python
PyData • Data Science, Machine Learning, Science, Data Engineering, Statistics14:35
Thorben Jensen (Informationsfabrik GmbH)
Automating feature engineering for supervised learning? Methods, open-source tools and prospects.
PyData • Artificial Intelligence, Algorithms, Data Science, Machine Learning, Data Engineering15:05
Enterprise
15:30
16:05
Cheuk Ting Ho
Running An Open Source Project Like A Start Up
PyConDE • Business & Start-Ups, Community, Data Science, Machine Learning11:20
12:45
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11:20
11:30
Sandrine Pataut (QBE Insurance)
Get to grips with pandas and scikit-learn
PyData • Algorithms, Data Science, Machine Learning13:00
13:50
15:05
15:20
Caio Miyashiro (Mytaxi)
Hidden Markov Models for Chord Recognition - Intuition and Applications
PyData • Algorithms, Data Science, Machine Learning, Statistics11:20
11:30
Steph Samson (Mercedes-Benz.io)
Package and Dependency Management with Poetry
PyConDE • DevOps, Infrastructure, Use Cases13:00
13:50
15:05
15:20
Thursday, October 10
talks/keynotes
center
Saal 2talks
front
Saal 10talks
front
Saal 6talks
back, middle
Saal 5talks
center
Loungediv
front
Saal 4Tutorial
back
Saal 7Tutorial
back
08:30
09:00
09:10
Gaussian Process
10:00
Vincent Warmerdam (GoDataDriven)
Gaussian Progress
PyData • Artificial Intelligence, Algorithms, Data Science, IDEs/ Jupyter, Machine Learning, Statistics10:50
Dr. Juan Orduz
Gaussian Process for Time Series Analysis
PyData • Algorithms, Data Science, Machine Learning, Statistics11:20
Vision
11:50
Marysia Winkels (Aidence)
Equivariance in CNNs: how generalising the weight-sharing property increases data-efficiency
PyData • Artificial Intelligence, Algorithms, Computer Vision, Deep Learning, Data Science, Machine Learning, Science12:25
Irina Vidal Migallón (Siemens Mobility GmbH)
Using adversarial samples to break and robustify your Vision Neural Network Models
PyData • Artificial Intelligence, Computer Vision, Deep Learning, Machine Learning13:00
Python
14:00
Alexander CS Hendorf (KÖNIGSWEG), Hynek Schlawack (Variomedia AG), Mariatta Wijaya (Zapier), Łukasz Langa (Python Software Foundation), Stefan Behel
Python Panel
PyConDE • Community14:35
15:05
Python
15:30
16:05
Christoph Heer (SAP SE)
Is it me, or the GIL?
PyConDE • Infrastructure, Parallel Programming, Visualisation16:50
17:00
Marie-Louise Timcke (FUNKE Zentralredaktion Berlin GmbH)
Extended Ligthning Talks CANCELLED: Crunching Numbers Like a Journalist
PyData • Big Data, Data Science, Statistics17:45
18:30
19:00
Docker
10:00
Dr. Hendrik Niemeyer (ROSEN Technology and Research Center GmbH)
Docker and Python - A Match made in Heaven
PyConDE • Big Data, DevOps, Infrastructure10:50
Sebastian Neubauer (Blue Yonder - A JDA Company)
6 Years of Docker: The Good, the Bad and Python Packaging
PyConDE • DevOps, Infrastructure, IDEs/ Jupyter, Use Cases11:20
Enterprise
11:50
Alexander CS Hendorf (KÖNIGSWEG)
Data Literacy for Managers
PyData • Artificial Intelligence, Business & Start-Ups, Data Science, Machine Learning, Use Cases12:25
Rachel Berryman (AI Guild), Dânia Meira (AI Guild)
Avoiding ML FOBO
PyData • Algorithms, Business & Start-Ups, Data Science, Machine Learning13:00
scikit*
14:00
Benjamin Bossan (NewYorker)
skorch: A scikit-learn compatible neural network library that wraps pytorch
PyData • Deep Learning, Data Science, Machine Learning14:35
Adrin Jalali (Anaconda Inc.)
Current affairs, updates, and the roadmap of scikit-learn and scikit-learn-contrib
PyData • Artificial Intelligence, Community, Code-Review, Machine Learning15:05
A bit of Theory
15:30
Benedikt Rudolph (Lucht Probst Associates)
Should I stay or should I go? Optimal exercise decisions using the Longstaff-Schwartz algorithm
PyData • Algorithms, Business & Start-Ups, Data Science, Science, Statistics16:05
Gönül Aycı (Bogazici University)
Active Learning with Bayesian Nonnegative Matrix Factorization for Recommender Systems
PyData • Statistics
Python's friends
10:00
Luciano Ramalho (ThoughtWorks)
Beyond Paradigms: a new key to grok Python & other languages
PyConDE • Algorithms, Code-Review10:50
11:20
API
11:50
12:25
13:00
Vision
14:00
Neslihan Edes (Ruhr-University Bochum)
Birds of a feather flock together - Tracking pigeons with Python and OpenCV
PyData • Computer Vision, IDEs/ Jupyter, Science14:35
Martin Christen (FHNW - University of Applied Sciences and Arts Northwestern Switzerland)
Detecting and Analyzing Solar Panels in Switzerland using Aerial Imagery
PyData • Big Data, Computer Vision, Deep Learning, Data Science, Machine Learning, Visualisation15:05
Good practices
15:30
Paloma (autonomous| part os PyLadies Berlin)
From body and code <programming in times of acceptance>
PyConDE • Business & Start-Ups, Community, Web16:05
ML & uncertainty
10:00
Florian Wilhelm (inovex)
Are you sure about that?! Uncertainty Quantification in AI
PyData • Artificial Intelligence, Deep Learning, Data Science, Machine Learning, Science10:50
Stefan Maier (Blue Yonder, a JDA company)
Embrace uncertainty! Why to go beyond point estimators for valuable ML applications
PyData • Algorithms, Data Science, Machine Learning, Statistics11:20
Visualization
11:50
Dom Weldon (decisionLab)
Dash: Interactive Data Visualization Web Apps with no Javascript
PyData • Data Science, Visualisation, Web12:25
Philipp Rudiger (Anaconda Inc.)
Panel: Turn any notebook into a deployable dashboard
PyData • Data Science, IDEs/ Jupyter, Visualisation13:00
Tests and *env
14:00
Sander Kooijmans (Protix)
How to write tests that need a lot of data?
PyData • Algorithms, Code-Review14:35
15:05
ML use-case
15:30
Nelson Mooren
Using Overhead Video Capture to Analyse Grouping Behaviour of Dancers in a Silent Disco
PyData • Computer Vision, Science16:05
Darina Goldin (Bayes Esports Solutions)
How strong is my opponent? Using Bayesian methods for skill assessment
PyData • Algorithms
Tools
10:00
Katharina Rasch
Tools that help you get your experiments under control
PyData • Artificial Intelligence, Data Science, DevOps, Infrastructure10:50
Jeremy Tuloup (QuantStack)
A Tour of JupyterLab Extensions
PyData • Community, Data Science, IDEs/ Jupyter, Visualisation11:20
ML for good
11:50
Ellen König (ThoughtWorks)
Want to have a positive social impact as a data scientist?
PyData • Community, Data Science12:25
Eva Schreyer (Data Science for Social Good Berlin DSSG), Lisa Zäuner
Tackle the problems that really matter - leverage the power of data science in the service of humanity
PyData • Business & Start-Ups, Community, Data Science13:00
Classificaion / FP
14:00
Johannes Knopp (solute)
10 Years of Automated Category Classification for Product Data
PyData • Artificial Intelligence, Deep Learning, Data Science, Infrastructure, Machine Learning, Data Engineering14:35
David Schmudde (Nextjournal)
Dr. Schmood's Notebook of Python Calisthenics and Orthodontia
PyConDE • Data Science, IDEs/ Jupyter15:05
Hardware
15:30
16:05
Dan Fritchman (HW21)
Chips Made From Python
PyConDE • Microcontrollers, Parallel Programming, Science, Makers
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11:20
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17:45
10:00
Enrica Pasqua (Delivery Hero SE), Bahadir Uyarer (Delivery Hero SE)
Airflow: your ally for automating machine learning and data pipelines
PyData • Big Data, Infrastructure, Machine Learning, Data Engineering11:20
11:30
Daniel Heinze (Microsoft)
Build a Machine Learning pipeline with Jupyter and Azure
PyData • Computer Vision, Deep Learning, DevOps, IDEs/ Jupyter, Machine Learning, APIs, Python13:00
13:45
Christian Barra (Infarm)
Kubernetes 101 for Python Developers
PyConDE • DevOps, Infrastructure, Web, APIs, Use Cases15:05
15:15
James Wootton (IBM Research)
Quantum computing with Python
PyData • Algorithms, Infrastructure, Microcontrollers, Science, APIs10:00
Pedro Saleiro (Feedzai)
Fairness in decision-making with AI: a practical guide & hands-on tutorial using Aequitas
PyData • Data Science, Machine Learning, Use Cases11:20
11:30
Tanmoy Bandyopadhyay (Aricent)
An Introduction to Concurrency and Parallelism using Python Programming Language
PyConDE • Algorithms, Parallel Programming13:00
13:45
15:05
15:15
16:00
Friday, October 11
talks/keynotes
center
Saal 2talks
front
Saal 10talks
front
Saal 6talks
back, middle
Saal 5talks
center
Loungediv
front
Saal 4Tutorial
back
Saal 7Tutorial
back
08:30
09:00
09:10
ML & Ethics
10:00
Dr. Benjamin Werthmann (werthmann.legal)
Law, ethics and machine learning – a curious ménage à trois
PyData • Artificial Intelligence, Big Data, Machine Learning10:50
Avaré Stewart (EOS DID (Otto Group))
Transforming a Legacy System into a Bias-Mitigating AI Solution for Debt Repayment
PyData • Artificial Intelligence, Data Science, Natural Language Processing, Machine Learning, Data Engineering11:20
Python
11:50
12:25
13:00
Work
14:00
Christian Barra (Infarm), Tereza Iofciu (mytaxi), Katharina Rasch, Matteo Guzzo, Sieer Angar
Job Panel
PyConDE • Business & Start-Ups14:35
15:05
15:30
15:45
16:15
16:45
Testing
10:00
Raphael Pierzina (Mozilla)
Introduction to automated testing with pytest
PyConDE • DevOps, Web, Data Engineering10:50
Oliver Bestwalter (Avira)
Abridged metaprogramming classics - this episode: pytest
PyConDE • Algorithms, Code-Review, APIs, Use Cases11:20
Input
11:50
Daniel Rios (Jonas und der Wolf)
Optimizing Input: Building your own customized keyboard
PyConDE • Community, Microcontrollers, Makers12:25
Miroslav Šedivý (solute GmbH)
Your Name Is Invalid!
PyData • Algorithms, Community, Natural Language Processing, Web, Data Mining / Scraping, Use Cases13:00
Interpretable ML
14:00
Alexander Engelhardt (Engelhardt Data Science GmbH)
Interpretable Machine Learning: How to make black box models explainable
PyData • Data Science, Machine Learning14:35
15:05
DB
10:00
Dmitry Nazarov (DataArt)
CANCELLED: Fresh New Pythonic Database: EdgeDB (And Why It's the Future)
PyConDE • Web, Use Cases10:50
Patrick Arminio (Verve)
Strawberry: a dataclasses inspired approach to GraphQL
PyConDE • Django, Web11:20
Lessons Learned
11:50
Samet Atdag (Prisync)
What we learned from scraping 1 billion webpages every month
PyConDE • Business & Start-Ups, Big Data, Infrastructure, Web, Data Engineering12:25
Gina Häußge (OctoPrint)
Driving 3D Printers with Python: Lessons Learned
PyConDE • Web, 3D Priniting, Makers13:00
NLP for good
14:00
Andrada Pumnea (Futurice GmbH)
Does hate sound the same in all languages?
PyData • Deep Learning, Data Science, Natural Language Processing, Data Mining / Scraping14:35
Teresa Ingram
The Sound of Silence: Online Misogyny and How we Model it
PyData • Community, Natural Language Processing, Machine Learning15:05
Production
10:00
Alessia Marcolini (Fondazione Bruno Kessler)
Version Control for Data Science
PyData • Artificial Intelligence, Data Science, Machine Learning10:50
Hari Kishore Sirivella (OpenTable Inc.)
Monitoring infrastructure and application using Django, Sensu and Celery.
PyConDE • Django, DevOps, Infrastructure11:20
PyMC
11:50
Korbinian Kuusisto (Dalia Research)
Leveraging the advantages of Bayesian Methods to build a data science product using PyMC3
PyData • Algorithms, Business & Start-Ups, Data Science, Machine Learning, Science, Statistics12:25
Corrie Bartelheimer (Europace AG)
A Bayesian Workflow with PyMC and ArviZ
PyData • Data Science, Statistics13:00
Visualization
14:00
Yuta Kanzawa (Janssen Pharmaceutical K.K., Tokyo; Johnson & Johnson)
Friend or Foe: Comparison of R & Python in Data Wrangling & Visualisation
PyData • Data Science, Machine Learning, Visualisation, Statistics14:35
Tania Vasilikioti (Babbel)
Making the complex simple in data viz
PyData • Data Science, Visualisation15:05
ML & RL
10:00
Yurii Tolochko (BASF)
Why you don’t see many real-world applications of Reinforcement Learning.
PyData • Artificial Intelligence, Algorithms, Deep Learning, Machine Learning, Statistics10:50
David Wölfle (FZI Research Center for Information Technology)
Loss Function Theory 101
PyData • Artificial Intelligence, Algorithms, Deep Learning, Data Science, Machine Learning, Statistics11:20
Carreer
11:50
Noa Tamir
Professional Development and Career Progression for Data Scientists
PyData • Business & Start-Ups, Community, Data Science12:25
Tereza Iofciu (mytaxi)
Lessons Learned as a Product Manager in Data Science
PyData • Business & Start-Ups, Data Science, Machine Learning13:00
ML use-case
14:00
Andreas Hantsch (CLOUD&HEAT Technologies GmbH)
Machine learning with little data - from digital twin to predictive maintenance
PyData • Deep Learning, Machine Learning, Science14:35
Peggy Sylopp (pexlab.space), Aislyn Rose
Take control of your hearing: Accessible methods to build a smart noise filter
PyData • Artificial Intelligence, Algorithms, Computer Vision, Deep Learning, Data Science, Machine Learning, Science15:05
11:20
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13:00
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10:00
Valentin Haenel (Anaconda Inc.)
CANCELED: Create CUDA kernels from Python using Numba and CuPy.
PyData • Algorithms, Big Data, Data Science, Parallel Programming11:20
11:30
Peter Kairouz (Google), Amlan Chakraborty
Decentralized and Privacy-Preserving ML via TensorFlow Federated
PyData • Artificial Intelligence, Deep Learning, Data Science, Machine Learning, Data Engineering13:00
13:45
Filipe Silva (FREE NOW)
Using machine learning for Level Generation in Snake (video-game)
PyData • Data Science, Machine Learning10:00
Tobias Sterbak (Freelancer @ depends-on-the-defintion)
Managing the end-to-end machine learning lifecycle with MLFlow
PyData • Data Science, Infrastructure, Machine Learning, Data Engineering11:20
11:30
Dominik Henter (Ecosia), Jéssica Lins (Ecosia)
Parallel programming for python developers – Let’s Go(lang)
PyConDE • Infrastructure, Networks, Parallel Programming13:00
13:45