{"id":224,"date":"2020-09-12T16:02:05","date_gmt":"2020-09-12T16:02:05","guid":{"rendered":"https:\/\/machine-learning.webcloning.com\/2020\/09\/12\/hyperopt-for-automated-machine-learning-with-scikit-learn\/"},"modified":"2020-09-12T16:02:05","modified_gmt":"2020-09-12T16:02:05","slug":"hyperopt-for-automated-machine-learning-with-scikit-learn","status":"publish","type":"post","link":"https:\/\/salarydistribution.com\/machine-learning\/2020\/09\/12\/hyperopt-for-automated-machine-learning-with-scikit-learn\/","title":{"rendered":"HyperOpt for Automated Machine Learning With Scikit-Learn"},"content":{"rendered":"
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Automated Machine Learning (AutoML) refers to techniques for automatically discovering well-performing models for predictive modeling tasks with very little user involvement.<\/p>\n

HyperOpt is an open-source library for large scale AutoML and HyperOpt-Sklearn is a wrapper for HyperOpt that supports AutoML with HyperOpt for the popular Scikit-Learn machine learning library, including the suite of data preparation transforms and classification and regression algorithms.<\/p>\n

In this tutorial, you will discover how to use HyperOpt for automatic machine learning with Scikit-Learn in Python.<\/p>\n

After completing this tutorial, you will know:<\/p>\n