今天在推上被一位朋友问到AutoML的入门资料，我想了一下之前看过第四范式的这篇Survey，他们一直在KDD Cup/NIPS上承办AutoML Challenge。这篇入门survey也是我看过的写得最好的，2018年11月提交，2019年1月最后一次revised，内容够新够全。https://arxiv.org/abs/1810.13306AutoML的很多工作都是集中于超参数调节，虽然我觉得它很多时候没有CV/NLP方向那么生动，却还是有自己很独特的魅力，落地价值也很强。

Data Science Archive

今天在推上被一位朋友问到AutoML的入门资料，我想了一下之前看过第四范式的这篇Survey，他们一直在KDD Cup/NIPS上承办AutoML Challenge。这篇入门survey也是我看过的写得最好的，2018年11月提交，2019年1月最后一次revised，内容够新够全。https://arxiv.org/abs/1810.13306
AutoML的很多工作都是集中于超参数调节，虽然我觉得它很多时候没有CV/NLP方向那么生动，却还是有自己很独特的魅力，落地价值也很强。

arXiv.org

Automated Machine Learning: From Principles to Practices

Machine learning (ML) methods have been developing rapidly, but configuring and selecting proper methods to achieve a desired performance is increasingly difficult and tedious. To address this...

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