Presented By O'Reilly and Cloudera
Make Data Work
Feb 17–20, 2015 • San Jose, CA
Andreas Mueller

Andreas Mueller
Maintainer | Core Contributor, NYU, scikit-learn

Website

Andreas Mueller received his PhD in machine learning from the University of Bonn. After working as a machine learning researcher on computer vision applications at Amazon for a year, he recently joined the Center for Data Science at New York University. In the last four years, he has been maintainer and one of the core contributors of scikit-learn, a machine learning toolkit widely used in industry and academia, and author and contributor to several other widely-used machine learning packages. His mission is to create open tools to lower the barrier of entry for machine learning applications, promote reproducible science, and democratize access to high-quality machine learning algorithms.

Sessions

9:00am–5:00pm Wednesday, 02/18/2015
Data Science
Location: LL21 B
Andreas Mueller (NYU, scikit-learn), Jennifer Klay (Cal Poly San Luis Obispo), Peter Wang (Anaconda), Travis Oliphant (Anaconda), Andy Terrel (NumFOCUS), Matthew Rocklin (Anaconda), Wes McKinney (Two Sigma Investments), Stefan van der Walt (UC Berkeley), Jonathan Frederic (IPython), Kyle Kelley (Netflix)
Average rating: ****.
(4.62, 8 ratings)
Python has become an increasingly important part of the data engineer and analytic tool landscape. Pydata at Strata provides in-depth coverage of the tools and techniques gaining traction with the data audience, including iPython Notebook, NumPy/matplotlib for visualization, SciPy, scikit-learn, and how to scale Python performance, including how to handle large, distributed data sets. Read more.
2:20pm–3:00pm Thursday, 02/19/2015
Ask Us Anything
Location: 211 B
Andreas Mueller (NYU, scikit-learn), Jennifer Klay (Cal Poly San Luis Obispo), Peter Wang (Anaconda), Travis Oliphant (Anaconda), Andy Terrel (NumFOCUS), Matthew Rocklin (Anaconda), Wes McKinney (Two Sigma Investments), Stefan van der Walt (UC Berkeley), Kyle Kelley (Netflix), Jonathan Frederic (IPython)
Average rating: *****
(5.00, 1 rating)
Join the presenters of the PyData Tutorials for further discussions on some of the most used tools in the Python data stack. This is a great opportunity to ask questions and share insight with those who have authored or contributed to: * scikit-learn * NumPy * Bokeh * IPython * Numba * Blaze * pandas * scikit-image Read more.