This post is the first place prize recipient in the recent KDnuggets blog contest. Auto-sklearn is an open-source Python tool that automatically determines effective machine learning pipelines for classification and regression datasets. It is built around the successful scikit-learn library and won the recent AutoML challenge.
Read a data-driven discussion on the plight of internally displaced persons (IDPs) in Nigeria, and see the real power of data science and data visualization.
This post is an overview of an automated machine learning system in the digital advertising realm. It is an entrant and second-place recipient in the recent KDnuggets blog contest.
This post discusses some considerations, options, and opportunities for automating aspects of data science and machine learning. It is the second place recipient (tied) in the recent KDnuggets blog contest.
This post evaluates several methods for automating the feature selection process in large-scale linear regression models and show that for marketing applications the winner is Stepwise regression.
This post provides a simplifying framework, an ontology for Machine Learning and some important developments in dynamical machine learning. From first hand Data Science product experience, the author suggests how best to execute Data Science projects.
Introducing Dataiku DSS 3.1, with new visual machine learning engines that allow users to create incredibly powerful predictive applications within a code-free interface.
