PyCon DE 2018


The annual PyCon in Germany. This year it was in Karlsrurh. It was a large well organized, well funded, and well run conference with lots of great talks.

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Sub Categories

Measuring the hay in the haystack: quantifying hidden variables using Bayesian Inference

Strongly typed datasets in a weakly typed world

Cloud chat bot for lazy people

Driving simulation and data analysis of magnetic nanostructures through Jupyter Notebook

Germany's next topic model

Active Learning - Building Semi-supervised Classifiers when Labeled Data is not Available

Reproducibility, and Selection Bias in Machine Learning

Testing in Python - The Big Picture

Beyond Jupyter Notebooks - Building your own Data Science platform with Python & Docker

PyLadies - Jessica Greene and PyLadies Berlin

Python Dependency Management

Python on the blockchain: Triumphs and tribulations in a crypto startup

Creating an inclusive corporate culture

Put your data on a map

Case Study in Travel Business - Understanding agent connections using NetworkX

Python Birdies: Codegolfing for better understanding (and fun)

Jupyter Notebook Best Practices

Python And PostgreSQL

Building your own conversational AI with open source tools

Keynote: Learning programming & science with Scientific Python

Stretchy - NoSQL Database behind REST API

Grammar of Graphics in Python

Script, Library, or Executable: You can have it all!

Experiences from applying Convolutional Neural Networks for classifying 2D sensor data

How to make your (digital) Communication strong & future ready

ZODB: The Graph Database for PythonDevelopers

Python with and without Pants

Closing Session

Prophet Fon Time Series: Do You Use It?

Selinon - dynamic distributed task flows

Enabling the chip technologies of tomorrow – how Python helps us

Solving Data Science Problems using a Jupyter Notebook and SAP HANA's in-database Machine Learning Libraries

Your first NLP project: peaks and pitfalls of unstructured data

Deep Learning with PyTorch for more Fun and Profit (Part II)

Processing Geodata using Python

Introduction and practical experience about Quantum Computing using the Python libraries from IBM and Google

Salabim, Discrete Event Simulation In Python

From exploration to deployment - combining PyTorch and TensorFlow for Deep Learning

Concurrency in Python - concepts, frameworks and best practices

Prototyping to tested code

Interactive Visualization of Traffic Data using Bokeh

Let Me Take A Quick Look Into The Data

Pyccel, a Fortran static compiler for scientific High-Performance Computing

From Wittgenstein to TensorFlow: The role of Domain Specific Languages and Language Design in Machine Learning

Satellite data is for everyone: insights into modern remote sensing research with open data and Python

Bonobo, Airflow and Grafana to visualize your business

Keynote: Looking backward, looking forward

Advanced Analytics Today: From Open Source Integration to the Operationalization of the Analytic Lifecycle

Data science complexity and solutions in real industrial projects

Binder - lowering the bar to sharing interactive software

Achieving Resilient Code with Integration Tests

PyTorch as a scientific computing library: past, present and future

Microservices from the trenches: how we delivery fancy sofas across Europe

Developing ecommerce platform with Django Oscar

reticulate: R interface to Python

Satellite Image Segmentation Photovoltaic Potential Estimation

Where the heck is my memory?

How to teach space invaders to your computer

Keynote: Digital Cultural Techniques

Fulfilling Apache Arrow's Promises: Pandas on JVM memory without a copy

Introduction to Docker for Pythonistas

About going Open-Source

Build text classification models ( CBOW and Skip-gram) with FastText in python

How type annotations make your code better

Distributed Hyperparameter search with sklearn and kubernetes

Data Science meets Data Protection: Keeping your data secure while learning from it.

Machine Learning as a Service: How to deploy ML Models as APIs without going nuts

A Day Has Only 24±1 Hours: import pytz

PyCon DE 2018 Lightenting Talks

Scalable Scientific Computing using Dask

Cython to speed up your Python code

Python Decorators: Gift or Poison?

What's new in Python 3.7?

Big Data Systems Performance: The Little Shop of Horrors

Productionizing your ML code seamlessly