📚 node [[parameter|parameter]]
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⥅ related node [[hyperparameter]]
⥅ related node [[parameter]]
⥅ related node [[parameter_server_(ps)]]
⥅ related node [[parameter_update]]
⥅ node [[parameter]] pulled by Agora
📓
garden/KGBicheno/Artificial Intelligence/Introduction to AI/Week 3 - Introduction/Definitions/Parameter.md by @KGBicheno
parameter
Go back to the [[AI Glossary]]
A variable of a model that the machine learning system trains on its own. For example, weights are parameters whose values the machine learning system gradually learns through successive training iterations. Contrast with hyperparameter.
⥅ node [[parameter_server_(ps)]] pulled by Agora
📓
garden/KGBicheno/Artificial Intelligence/Introduction to AI/Week 3 - Introduction/Definitions/Parameter_Server_(Ps).md by @KGBicheno
Parameter Server (PS)
Go back to the [[AI Glossary]]
A job that keeps track of a model's parameters in a distributed setting.
See the TensorFlow Architecture chapter in the TensorFlow Programmers Guide for details.
⥅ node [[parameter_update]] pulled by Agora
📓
garden/KGBicheno/Artificial Intelligence/Introduction to AI/Week 3 - Introduction/Definitions/Parameter_Update.md by @KGBicheno
parameter update
Go back to the [[AI Glossary]]
The operation of adjusting a model's parameters during training, typically within a single iteration of gradient descent.
📖 stoas
- public document at doc.anagora.org/parameter|parameter
- video call at meet.jit.si/parameter|parameter
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