Machine learning models are often inscrutable and it can be difficult to know whether you are making progress. To improve feedback and speed up iteration cycles Benjamin Bengfort and Rebecca Bilbro built Yellowbrick to easily generate visualizations of model performance. In this episode they explain how to use Yellowbrick in the process of building a machine learning project, how it aids in understanding how different parameters impact the outcome, and the improved understanding among teammates that it creates. They also explain how it integrates with the scikit-learn API, the difficulty of producing effective visualizations, and future plans for improvement and new features.

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GoCD is the on-premise open source continuous delivery server created by ThoughtWorks and modeled after the ideas in the Continuous Delivery book by Jez Humble and David Farley.

With GoCD’s comprehensive pipeline modeling, you can model complex workflows for multiple teams with ease. And GoCD’s Value Stream Map lets you track a change from commit to deploy at a glance.

GoCD’s real power is in the visibility it provides over your end-to-end workflow. So you get complete control of and visibility into your deployments, across multiple teams.

Say goodbye to deployment panic and hello to consistent, predictable deliveries.

To learn more about GoCD, visit gocd.org for a free download. Professional Support and enterprise add-ons, including disaster recovery, are available.