Industrial uses of Scikit-Learn (business roundtable)

Out-of-core NumPy arrays without changing your code with wendelin-core

Numba, a JIT compiler for fast numerical code

Pythran: Static Compilation of Parallel Scientific Kernels

scikit-learn for predictive maintenance at Airbus

Using Python and Data science to tackle real-time transportation problems at Lyft

Python, SQLalchemy and Scrapy for real-time data processing at Kpler

Embarrassingly parallel database calls with Python

Industrial Monitoring with the Wendelin Big Data platform

Simulating and visualising commuter flow through the London Underground

Why and how to explain machine learning predictions

Introduction to Pandas

Reaching your DREAMs with Python

Tree models with scikit-learn

Cleaning Confused Collections of Characters

Closing Keynote - Francesc Alted, UberResearch GmbH

Introduction to scikit-image

Opening Keynote - Gaël Varoquaux, Inria

Linear predictions with scikit-learn: simple and efficient