This talk will provide a brief introduction into scikit-learn and it's part in the machine learning ecosystem. It will also discuss recent additions to scikit-learn, such as better integration with pandas and better support for missing values and categorical data. We'll end some future directions, including better control over parallelization and better use of multi-core systems, as well as better tools for model inspection and model debugging.
Andreas Mueller is a lecturer at the Data Science Institute at Columbia University and author of the O'Reilly book "Introduction to machine learning with Python", describing a practical approach to machine learning with python and scikit-learn. He is one of the core developers of the scikit-learn machine learning library, and has been co-maintaining it for several years. He is also a Software Carpentry instructor. In the past, he worked at the NYU Center for Data Science on open source and open science, and as Machine Learning Scientist at Amazon.
Data Council, PO Box 2087, Wilson, WY 83014, USA - Phone: +1 (415) 800-4938 - EIN: 46-3540315 - Email: community (at) datacouncil.ai