What's New in Scikit-learn 0.15 and What's Cooking in the Development Branch?
Wednesday, August 13, 2014
Presented by: Olivier Grisel
Duration: Approximately 60 minutes.
Hosted By: Ben Lorica
This webcast will introduce scikit-learn, an Open Source project for Machine Learning in Python and review some new features from the recent 0.15 release such as faster randomized ensemble of decision trees and optimization for the memory usage when working on multiple cores.
We will also review on-going work part of the 2014 edition of the Google Summer of Code: neural networks, extreme learning machines, improvements for linear models, and approximate nearest neighbor search with locality-sensitive hashing.
About Olivier Grisel
Olivier Grisel is a software engineer at Inria Saclay, France. He works on scikit-learn an Open Source project for Machine Learning in Python. He also contributes occasional bug fixes to upstream projects in the NumPy / SciPy ecosystem.
About Ben Lorica
Ben Lorica is the Chief Data Scientist and Director of Content Strategy for Data at O'Reilly Media, Inc.. He has applied Business Intelligence, Data Mining, Machine Learning and Statistical Analysis in a variety of settings including Direct Marketing, Consumer and Market Research, Targeted Advertising, Text Mining, and Financial Engineering. His background includes stints with an investment management company, internet startups, and financial services. He writes regularly about Big Data and Data Science on the O'Reilly Data blog.
You may also be interested in:
Questions? Please send email to