Schedule

Wednesday 24.10.2018

# Media Theatre Lecture Hall Kubus Media Lounge Open Hub
09:00 Registration
09:30 Coffee
10:15 Opening
10:30

Keynote

11:30 Modern asynchronous programming
Andrew Svetlov
Parallel Programming, Web
Introduction and practical experience about Quantum Computing using the Python libraries from IBM and Google
Dr. Andreas Riegg
Jupyter, Programming, Python, Science
Your first NLP project: peaks and pitfalls of unstructured data
Anna Widiger
NLP
reticulate: R interface to Python
Jens Bruno Wittek
Artificial Intelligence, Algorithms, Big Data, Deep Learning & Artificial Intelligence, Data Science, NLP, Machine Learning, Visualisation
Pandas IO Tools: Reading and Writing DataFrames as Files and Databases
Miroslav Šedivý
Data Science, Jupyter, Science
12:15 Developing ecommerce platform with Django Oscar
Alexander Gaevsky
Business & Start-Ups, Code-Review, Django
Karabo - A control framework fueled by Python asyncio
Dennis Göries
Business & Start-Ups, Infrastructure, Science
Germany's next topic model
Thomas Mayer
Artificial Intelligence, Deep Learning & Artificial Intelligence, Data Science, Networks, NLP, Machine Learning, Visualisation
IoT using Python on Linux: Lessons Learned
Thomas Keppler, Matthias Schmidt
DevOps, Infrastructure, Networks, Programming, Python
13:00

Lunch Break

14:00 Performance evaluation of GANs in a semi-supervised OCR use case
Florian Wilhelm
Artificial Intelligence, Computer Vision, Deep Learning & Artificial Intelligence, Data Science, Machine Learning
Cython to speed up your Python code
Stefan Behnel
Big Data, Infrastructure, Jupyter, Parallel Programming
Build text classification models ( CBOW and Skip-gram) with FastText in python
Kajal Puri
Artificial Intelligence, Deep Learning & Artificial Intelligence, Data Science, NLP, Machine Learning
Finance, Sales and Business Development for Start-Ups
Ingo Stegmaier
Business & Start-Ups, Infrastructure
14:45 Active Learning - Building Semi-supervised Classifiers when Labeled Data is not Available
Dr. Hendrik Niemeyer
Artificial Intelligence, Algorithms, Data Science, Machine Learning, Python
Selinon - dynamic distributed task flows
Fridolín Pokorný
Big Data, Infrastructure, Parallel Programming, Programming, Python
Experiences from applying Convolutional Neural Networks for classifying 2D sensor data
Matthias Peussner
Artificial Intelligence, Computer Vision, Deep Learning & Artificial Intelligence, Machine Learning
15:40 Coffee Break
16:00 What's new in Python 3.7?
Stephane Wirtel
Community, Django, DevOps
Integration Tests with Super Powers
Alexandre Figura
Programming, Python
Case Study in Travel Business - Understanding agent connections using NetworkX
Cheuk Ting Ho
Algorithms, Networks, Python
Script, Library, or Executable: You can have it all!
Luke Lee
Programming, Python
Build a modern data infrastructure
Christian Barra
Big Data, Data Science, DevOps, Infrastructure, Jupyter, Web
16:30 Python Dependency Management
Patrick Muehlbauer
Infrastructure
Testing in Python - The Big Picture
Niklas Meinzer
Programming, Python
Binder - lowering the bar to sharing interactive software
Tim Head
Community, Data Science, DevOps, Jupyter, Science, Web
Productionizing your ML code seamlessly
Lauris Jullien
Artificial Intelligence, Data Science, Machine Learning
17:00 Distributed Hyperparameter search with sklearn and kubernetes
Jakob Karalus
Algorithms, Big Data, Data Science, DevOps, Infrastructure, Machine Learning
About going Open-Source
Tim
Business & Start-Ups
Pyccel, a Fortran static compiler for scientific High-Performance Computing
Dr. Ing. Ratnani Ahmed
Artificial Intelligence, Algorithms, Astronomy, Parallel Programming, Programming, Python, Science
How type annotations make your code better
Igor Davydenko
Infrastructure, Web
17:30 Lightning Talks
18:15 End
# TBA
19:00 Meetup

Thursday 25.10.2018

# Media Theatre Lecture Hall Kubus Media Lounge Open Hub
08:45 Morning Announcements
09:00

Keynote: Wes McKinney

10:00 Coffee
10:30 Deep Learning with PyTorch for more Fun and Profit (Part II)
Alexander CS Hendorf
Bonobo, Airflow and Grafana to visualize your business
Romain Dorgueil
Business & Start-Ups, Data Science, Visualisation, Web
Big Data Systems Performance: The Little Shop of Horrors
Jens Dittrich
Algorithms, Big Data, Data Science, Infrastructure, Parallel Programming, Programming, Python, Science
Write your Own Decorators
Mike Müller
Algorithms, Programming, Python
11:15 Reproducibility, and Selection Bias in Machine Learning
Valerio Maggio
Algorithms, Machine Learning, Science
Python with and without Pants
Stephan Erb
DevOps, Infrastructure
ZODB: The Graph Database for PythonDevelopers
Christopher Lozinski
Web
11:45 Data science complexity and solutions in real industrial projects
Artur Miller
Algorithms, Big Data, Data Science, Infrastructure, Machine Learning
A Day Has Only 24±1 Hours: import pytz
Miroslav Šedivý
Data Science, Science
Interactive Visualization of Traffic Data using Bokeh
Dr. Patrik Hlobil
Data Science, Visualisation, Web
Satellite Image Segmentation Photovoltaic Potential Estimation
Johannes Oos
Artificial Intelligence, Computer Vision, Deep Learning & Artificial Intelligence, Machine Learning, Science
13:00

Lunch Break

14:00 PyTorch as a scientific computing library: past, present and future
Adam Paszke
Python on the blockchain: Triumphs and tribulations in a crypto startup
Daniel and Lorb
Business & Start-Ups, Community, Django, Infrastructure, Python
Advanced Analytics Today: From Open Source Integration to the Operationalization of the Analytic Lifecycle
Tamara Fischer
Beyond Jupyter Notebooks - Building your own Data Science platform with Python & Docker
Joshua Görner
Artificial Intelligence, Algorithms, Data Science, DevOps, Infrastructure, Jupyter, Machine Learning, Programming, Python
Understanding Neural Networks by Playing Games
Sidharth Ramachandran
Artificial Intelligence, Deep Learning & Artificial Intelligence
14:45 Fulfilling Apache Arrow's Promises: Pandas on JVM memory without a copy
Uwe L. Korn
Algorithms, Big Data, Data Science, Parallel Programming
Data Science meets Data Protection: Keeping your data secure while learning from it.
Andreas Dewes, Katharine Jarmul
Artificial Intelligence, Business & Start-Ups, Big Data, Data Science
Processing Geodata using Python
Martin Christen
Big Data, Data Science, Jupyter, Python, Visualisation
Introduction to Docker for Pythonistas
Jan Wagner
Big Data, Data Science, DevOps, Jupyter, Machine Learning
15:15 Put your data on a map
Alex Vykaliuk
How to start business with Corporates
Martin Büllesbach
Business & Start-Ups, Community
Stretchy - NoSQL Database behind REST API
Artur Scholz
Big Data, Data Science, Web
Python Birdies: Codegolfing for better understanding (and fun)
Jonathan Oberländer
Algorithms
15:40 Coffee Break
16:00 How to teach space invaders to your computer
David Wölfle
Deep Learning & Artificial Intelligence, Jupyter, Python, Science
Creating an inclusive corporate culture
Yenny Cheung
Business & Start-Ups, Community
Observe all your applications
Christoph Heer
DevOps, Infrastructure, Networks, Programming, Python
Designing RESTful APIs
Anand Chitipothu
Python, Web
16:30 Driving simulation and data analysis of magnetic nanostructures through Jupyter Notebook
Hans Fangohr
Data Science, Jupyter, Programming, Python, Science
bericht - incremental HTML to PDF converter from scratch
Marius Räsener
Business & Start-Ups, Visualisation
Solving Data Science Problems using a Jupyter Notebook and SAP HANA's in-database Machine Learning Libraries
Dr Frank Gottfried
Big Data, Data Science, Jupyter, Machine Learning, Visualisation
17:00 Cloud chat bot for lazy people
Björn Meier
DevOps, Infrastructure
Where the heck is my memory?
Florian Jetter
Big Data, DevOps, Infrastructure
Expertise vs Experts
Yegor Bugayenko
17:30 Lightning Talks
18:15 End
# TBA
19:00 Social Event

Friday 26.10.2018

# Media Theatre Lecture Hall Kubus Media Lounge Open Hub
08:45 Morning Announcements
09:00

Keynote: Emmanuelle Gouillart

10:00 Coffee
10:30 Tickling not too thick ticks!
Giovanni Lanzani
DevOps, Parallel Programming
Building your own conversational AI with open source tools
Justina Petraitytė
Artificial Intelligence, NLP, Machine Learning, Python
Bokeh: using python for interactive data visualization
Ernesto Arbitrio
Data Science, Jupyter, Visualisation
11:15 Get your code out there
Tim Hoffmann
Data Science
Python Decorators: Gift or Poison?
Anastasiia Tymoshchuk
Python
Suggestions from Python and Solr
Jonathan Oberländer, Patrick Schemitz
Algorithms
Strongly typed datasets in a weakly typed world
Marco Neumann
Algorithms, Big Data, Data Science, Parallel Programming
11:45 Grammar of Graphics in Python
Malte Harder
Visualisation
Coding initiatives for kids: why you should get involved
Jackie Van der Steege
Community, Robotics
Satellite data is for everyone: insights into modern remote sensing research with open data and Python
Felix M. Riese, Jens Leitloff
Artificial Intelligence, Computer Vision, Deep Learning & Artificial Intelligence, Data Science, Machine Learning, Science
13:00

Lunch Break

14:00 Bayesian Inference with PyMC3
Holger Peters
Artificial Intelligence, Algorithms, Data Science, Machine Learning
Concurrency in Python - concepts, frameworks and best practices
Stefan Schwarzer
Parallel Programming, Programming, Python
From exploration to deployment - combining PyTorch and TensorFlow for Deep Learning
Marcel Kurovski
Artificial Intelligence, Deep Learning & Artificial Intelligence, Data Science, Machine Learning
Scalable Scientific Computing using Dask
Uwe L. Korn
Algorithms, Big Data, Data Science, Parallel Programming, Python
How to develop your project from an idea to architecture design in 50 minutes
Anastasiia Tymoshchuk, Elena Volovicheva
Programming
14:45 Designing better drugs with machine learning
Daniel Kuhn
Artificial Intelligence, Deep Learning & Artificial Intelligence, Data Science, Jupyter, Machine Learning, Science
Processing Geodata using Python
Martin Christen
Big Data, Data Science, Jupyter, Python, Visualisation
Machine Learning as a Service: How to deploy ML Models as APIs without going nuts
Anand Chitipothu
Machine Learning, Python, Web
15:15 Measuring the hay in the haystack: quantifying hidden variables using Bayesian Inference
Omer Yuksel
Data Science, Networks
Prototyping to tested code
Christopher Prohm
Data Science, Machine Learning
How to write 15 tests in 15 minutes
Suryansh Tibarewala
Community, Code-Review
15:40 Coffee Break
16:00 Lightning Talks
16:30 Closing Session
17:00 End

Saturday 27.10.2018

# TBA
10:00 Sprint & Hackathon
12:30 Lunch Break
13:30 Sprint & Hackathon
18:00 End

Sunday 28.10.2018

# TBA
10:00 Sprint & Hackathon
12:30 Lunch Break
13:30 Sprint & Hackathon
17:00 End