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Our Summer 2017 release presents Deepnets, a highly effective supervised learning method that solves classification and regression problems in a way that can match or exceed human performance, especially in domains where effective feature engineering is difficult. BigML Deepnets bring two unique parameter optimization options: Automatic Network Search and Structure Suggestion. These options avoid the difficult and time-consuming work of hand-tuning the algorithm and ensure the best network among all possible networks to solve your problem. This new resource is available from the BigML Dashboard, API, as well as from WhizzML for its automation. Deepnets are state-of-the-art in many important supervised learning applications.
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