News from Scikit-Learn 0.16 and Soon-To-Be Gems for the Next Release
Date: This event took place live on April 02 2015
Duration: Approximately 60 minutes.
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Hosted By: Ben Lorica
This webcast will review Scikit-learn, a widely used open source machine learning library in python, and discuss some of the new features of the recent 0.16 release. Highlights of the last release include new algorithms such as approximate nearest neighbors search, Birch clustering and a path algorithm for logistic regression, probability calibration, as well as improved ease of use and interoperability with the Pandas library.
We will also highlight some up-and-coming contributions, such as Latent Dirichlet Allocation, supervised neural networks, and a complete revamping of the Gaussian Process module.
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 Andreas Mueller
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 the New York University. In the last four years, he has been maintainer and one of the core contributor 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 the access to high-quality machine learning algorithms.
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 is an advisor to Databricks.