PyCon.DE 2018: Building Your Own Data Science Platform With Python & Docker - Joshua Görner
PyCon.DE 2018: Solving Data Science Probs With A Jupyter Notebook And SAP HANA's Libs - F. Gottfried
PyCon.DE 2018: Building Your Own Conversational AI With Open Source Tools - Justina Petraitytė
Building Your Own Data Science Platform With Python & Docker
PyCon.DE 2018: Introduction To Docker For Pythonistas - Jan Wagner
Skipper Seabold - Introduction to Python for Data Science - PyCon 2018
PyCon.DE 2018: Keynote - Wes McKinney
Noa Tamir: Professional Development and Career Progression for Data Scientists | PyData Berlin 2019
PyCon.DE 2018: Python With And Without Pants - Stephan Erb
PyCon.DE 2018: What's New In Python 3.7? - Stephane Wirtel
PyCon.DE 2018: Combining PyTorch And TensorFlow For Deep Learning - Marcel Kurovski
PyCon.DE 2018: About Going Open-Source - Tim
Melissa Weber Mendonça: Beyond the basics: Contributor experience, diversity and culture in open...
PyCon.DE 2018: Where The Heck Is My Memory? - Florian Jetter
PyCon.DE 2018: Python And PostgreSQL - Stephane Wirtel
PyCon.DE 2018: Fulfilling Apache Arrow's Promises: Pandas On JVM Memory Without A Copy - Uwe L. Korn
The Data Analytics Platform or How to Make Data Science in a Box Possible - Krzysztof Adamski
PyCon.DE 2018: Data Science Complexity And Solutions In Real Industrial Projects - Artur Miller
PyCon.DE 2018: How To Deploy ML Models As APIs Without Going Nuts - Anand Chitipothu
Dmitry Filippov, Ewa Jodlowska - By the Numbers: Python Community Trends in 2017/2018 - PyCon 2018