Posted by As announced in our latest blog posts, Boosted Trees is the new supervised learning technique that BigML offers to help you solve your classification and regressions problems. And it is now up and running as part of our set of ensemble-based strategies available through the BigML Dashboard and our REST API.
If you missed the webinar that was broadcasted yesterday, here you have another chance to follow our latest addition. In fact, you can play it anytime you wish since it’s available on the BigML Youtube channel.
Please visit our dedicated Winter 2017 Release page for more learning resources, including:
- The Boosted Trees documentation to learn how to create, interpret and make predictions with this algorithm, from both the BigML Dashboard and the BigML API.
- The series of six blog posts that guide you in the Boosted Trees journey step by step. Starting with the basic concepts of this algorithm and the differences between the other ensembles we offer; continuing with a use case and several examples of how to use Boosted Trees through the Dashboard, API, or how to automate the workflows with WhizzML and the Python Bindings; and finally wrapping up with the most technical side of how Boosted Trees work behind the scenes.
Many thanks for your attention, your questions, and the positive feedback after the webinar. We cannot wait to announce the next release!
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