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