PyConDE & PyData Berlin 2019

Talk PyData

Hide Code, Minimize Dependencies, Boost Performance - The PyTorch JIT

Tilman Krokotsch

Artificial Intelligence, Deep Learning, Data Science, Machine Learning

PyTorch makes developing, training and debugging deep neural networks convenient. Learn how to export your trained model using its just-in-time (JIT) compiler to hide your network architecture, minimize code dependencies and use it in the C++ API. It's getting faster, too!

Talk PyData

How to choose better colors for your data visualizations

Daniel Ringler

Data Science, Visualisation

You want to choose better colors for all the charts that you create with Python but you do not know where to start? This talk will teach you some basics about color theory so your charts will show what is important (and look beautiful).

Talk PyConDE

Mock Hell

Edwin Jung

Code-Review, Web, Data Engineering

Mock Hell: How to escape and avoid it, and improve your design in the process.

Talk PyData

Practical DevOps for the busy data scientist

Dr. Tania Allard

Algorithms, Big Data, Data Science, DevOps, Machine Learning

Devops for the busy data scientist: learn how to leverage these practices to improve your workflows

Talk PyData

Time series modelling with probabilistic programming

Sean Matthews, Jannes Quer

Data Science, Statistics

Probabilistic time-series forecasting @ Deloitte Analytics Institute