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	Podcast:		Machine Learning – Software Engineering Daily
	Episode:		Hyperparameter Tuning with Richard Liaw
	Category:		Technology
	Duration:		00:53:33
	Publish Date:		2020-08-28 09:00:50
	Description:		Hyperparameters define the strategy for exploring a space in which a machine learning model is being developed. Whereas the parameters of a machine learning model are the actual data coming into a system, the hyperparameters define how those data points are fed into the training process for building a model to be used by an end consumer. A different set of hyperparameters will yield a different model. Thus, it is important to try different hyperparameter configurations to see which models end up performing better for a given application. Hyperparameter tuning is an art and a science. Richard Liaw is an engineer and researcher, and the creator of Tune, a library for scalable hyperparameter tuning. Richard joins the show to talk through hyperparameters and the software that he has built for tuning them. Sponsorship inquiries: sponsor@softwareengineeringdaily.com The post Hyperparameter Tuning with Richard Liaw appeared first on Software Engineering Daily.
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