PyData Berlin 2016
May 20th - 21st
Talks
Using small data in the client instead of big data in the cloud
Anton Dubrau
Predictive modelling with Python
Olivier Grisel (keynote)
Frontera: open source, large scale web crawling framework
Alexander Sibiryakov
Functional Programming in Python
Daniel Kirsch
One in a billion: finding matching images in very large corpora
Ryan Henderson
Dealing with TBytes of Data in Realtime
Nils Magnus
Classifying Search Queries Without User Click Data
Abhishek Thakur
BigchainDB : a Scalable Blockchain Database, in Python
Trent McConaghy
How to Trick a Neural Network
Julia Evans (keynote)
Machine Learning at Scale
Nathan Epstein
What every data scientist should know about data anonymization
Katharina Rasch
Accelerating Python Analytics by In-Database Processing
Edouard Fouché
Python and TouchDesigner for Interactive Experiments
Jessica Palmer
Let's play Space Invaders!
Maciej Jaskowski
Python Data Ecosystem: Thoughts on Building for the Future
Wes McKinney (keynote)
What's new in Deep Learning?
Kashif Rasul
Designing spaCy: Industrial-strength NLP
Matthew Honnibal
Data Integration in the World of Microservices
Valentine Gogichashvili
Bridging the gap: from Data Science to service
Daniel Moisset
The "Kwargh!" Problem
James Powell
Usable A/B testing – A Bayesian approach
Nora Neumann
Introduction to Julia for Python Developers
David Higgins
Robot uses toddler-like self exploration for the development of body representations
Idai Guertel
pypet: A Python Toolkit for Simulations and Numerical Experiments
Robert Meyer
PySpark in Practice
Ronert ObstDat Tran
Zero-Administration Data Pipelines using AWS Simple Workflow
Anne Matthies
Visualizing research data: Challenges of combining different datasources
Juha Suomalainen
Spotting trends and tailoring recommendations: PySpark on Big Data in fashion
Martina Pugliese
Smart Banking - Real Time Driven
Arnab DuttaChristian Rebernik
Visualizing FragDenStaat.de
Andrej Warkentin
Plumbing in Python: Pipelines for Data Science Applications
Thomas Reineking
Bayesian Optimization and it's application to Neural Networks
Moritz Neeb
Python based predictive analytics with GraphLab Create
Danny Bickson
A full Machine learning pipeline in Scikit-learn vs in scala-Spark: pros and cons
Jose Quesada
Connecting Keywords to Knowledge Base Using Search Keywords and Wikidata
Fang Xu
Predicting political views from text
Felix Biessmann
Estimating stock price correlations using Wikipedia
Delia Rusu
Brand recognition in real-life photos
Lukasz Czarnecki
Building a polyglot Data Science Platform on Big Data systems
Frank Kaufer
Removing Soft Shadows with Hard Data
Maciej Gryka
ExpAn - A Python library for advanced statistical analysis of A/B tests
Jie Bao
Setting up predictive analytics services with Palladium
Andreas Lattner