PyData Berlin 2014

URL:
http://pydata.org/berlin2014/
Description:

PyData conferences are a gathering of users and developers of data analysis tools in Python. The goals are to provide Python enthusiasts a place to share ideas and learn from each other about how best to apply the language and tools to ever-evolving challenges in the vast realm of data management, processing, analytics, and visualization.

Date:
July 25, 2014
Number of videos:
33
Metadata
JSON
Building the PyData Community
PyData Berlin 2014
Travis Oliphant
Recorded: July 27, 2014Language: English
Commodity Machine Learning
PyData Berlin 2014
Andreas Mueller
Recorded: July 27, 2014Language: English
Exploring Patent Data with Python
PyData Berlin 2014
Franta Polach
Recorded: July 27, 2014Language: English

Experiences from building a recommendation engine for patent search using pythonic NLP and topic modeling tools such as Gensim.

Intro to ConvNets
PyData Berlin 2014
Kashif Rasul
Recorded: July 27, 2014Language: English

We will give an introduction to the recent development of Deep Neural Networks and focus in particular on Convolution Networks which are well suited to image classification problems. We will also provide you with the practical knowledge of how to get started with using ConvNets via the cuda-convnet python library.

IPython and Sympy to Develop a Kalman Filter for Multisensor Data Fusion
PyData Berlin 2014
Paul Balzer
Recorded: July 27, 2014Language: English

The best filter algorithm to fuse multiple sensor informations is the Kalman filter. To implement it for non-linear dynamic models (e.g. a car), analytic calculations for the matrices are necessary. In this talk, one can see, how the IPython Notebook and Sympy helps to develop an optimal filter to fuse sensor information from different sources (e.g. acceleration, speed and GPS position) to get an optimal estimate. more: http://balzer82.github.io/Kalman/

Lightning Talks
PyData Berlin 2014
Recorded: July 27, 2014Language: English
Make sense of your (big) data using Elasticsearch
PyData Berlin 2014
Honza Král
Recorded: July 27, 2014Language: English

In this talk I would like to show you a few real-life use-cases where Elasticsearch can help you make sense of your data. We will start with the most basic use case of searching your unstructured data and move on to more advanced topics such as faceting, aggregations and structured search. I would like to demonstrate that the very same tool and dataset can be used for real-time analytics as well as the basis for your more advanced data processing jobs. All in a distributed environment capable of handling terabyte-sized datasets. All examples will be shown with real data and python code demoing the new libraries we have been working on to make this process easier.

Pandas' Thumb: unexpected evolutionary use of a Python library.
PyData Berlin 2014
Chris Nyland
Recorded: July 27, 2014Language: English

This talk is a description of how - against a backdrop of data-drunk tax authorities, legal pressures on businesses to have appropriate compliance systems in place, and the constant pressure on their law firms to commoditise compliance services, Pandas may be about to make a foray from its venerable financial origins into a brave new fiscal world - and can revolutionise an industry by doing so. A case study covering the author's development of a Pandas-based stamp duty land tax engine ("ORVILLE") is discussed, and the inherent usefulness of Pandas in the world of tax analysis is explored.

Algorithmic Trading with Zipline
PyData Berlin 2014
Thomas Wiecki
Recorded: July 26, 2014Language: English
Data Oriented Programming
PyData Berlin 2014
Francesc Alted
Recorded: July 26, 2014Language: English
Dealing With Complexity
PyData Berlin 2014
Jean-Paul Schmetz
Recorded: July 26, 2014Language: English
Driving Moore's Law with Python-Powered Machine Learning: An Insider's Perspective
PyData Berlin 2014
Trent McConaghy
Recorded: July 26, 2014Language: English

People talk about a Moore's Law for gene sequencing, a Moore's Law for software, etc. This is talk is about the Moore's Law, the bull that the other "Laws" ride; and how Python-powered ML helps drive it. How do we keep making ever-smaller devices? How do we harness atomic-scale physics? Large-scale machine learning is key. The computation drives new chip designs, and those new chip designs are used for new computations, ad infinitum. High-dimensional regression, classification, active learning, optimization, ranking, clustering, density estimation, scientific visualization, massively parallel processing -- it all comes into play, and Python is powering it all.

Extract Transform Load using mETL
PyData Berlin 2014
Bence Faludi
Recorded: July 26, 2014Language: English
Generators Will Free Your Mind
PyData Berlin 2014
James Powell
Recorded: July 26, 2014Language: English
How to Spy with Python
PyData Berlin 2014
Lynn Root
Recorded: July 26, 2014Language: English

This talk will walk through what the US government has done in terms of spying on US citizens and foreigners with their PRISM program, then walk through how to do exactly that with Python.

Low-rank matrix approximations in Python
PyData Berlin 2014
Christian Thurau
Recorded: July 26, 2014Language: English
Packaging and Deployment
PyData Berlin 2014
Travis Oliphant
Recorded: July 26, 2014Language: English
Speed Without Drag
PyData Berlin 2014
Saul Diez-Guerra
Recorded: July 26, 2014Language: English

Speed without drag: making code faster when there's no time to waste A practical walkthrough over the state-of-the-art of low-friction numerical Python enhancing solutions, covering: exhausting CPython, NumPy, Numba, Parakeet, Cython, Theano, Pyston, PyPy/NumPyPy and Blaze.

Street Fighting Trend Research
PyData Berlin 2014
Benedikt Koehler
Recorded: July 26, 2014Language: English

This talk shows how to tackle common tasks in applied trend research and technology foresight from identifying a data-source, getting the data and data cleaning to presenting the insights in meaningful visualizations.

Visualising Data through Pandas
PyData Berlin 2014
Vincent Warmerdam
Recorded: July 26, 2014Language: English

pandas & ggplot: quick analysis with python and friends