Hyperparameter Tuning with Katib
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80 дней – 9250:58Опубликовано 20 июня 2020, 23:00
Getting started with Katib → goo.gle/3hI9sFi
How do you go about setting the number of epochs you want to train? What about choosing the type of optimization functions you want to use? When it comes to machine learning, it can be difficult to know what values will yield the results you want. In this episode of Kubeflow 101, Stephanie Wong shows you what hyperparameters are and how Katib can help your machine learning efforts. Watch as Stephanie demos Katib, showing how this tool can help you tune your hyperparameters and give insight on how different values affect your overall objective.
Kubeflow GitHub example → goo.gle/3dfHCxB
Watch more episodes of Kubeflow 101 → goo.gle/3cqY2lR
Subscribe to the GCP Channel → goo.gle/GCP
Product: Kubeflow, Katib; fullname: Stephanie Wong;
#Kubeflow101
How do you go about setting the number of epochs you want to train? What about choosing the type of optimization functions you want to use? When it comes to machine learning, it can be difficult to know what values will yield the results you want. In this episode of Kubeflow 101, Stephanie Wong shows you what hyperparameters are and how Katib can help your machine learning efforts. Watch as Stephanie demos Katib, showing how this tool can help you tune your hyperparameters and give insight on how different values affect your overall objective.
Kubeflow GitHub example → goo.gle/3dfHCxB
Watch more episodes of Kubeflow 101 → goo.gle/3cqY2lR
Subscribe to the GCP Channel → goo.gle/GCP
Product: Kubeflow, Katib; fullname: Stephanie Wong;
#Kubeflow101
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