What are the different optimizers available in TensorFlow.js?
TensorFlow.js offers several optimizers like SGD, Adam, and RMSprop. Each has its own advantages depending on the task.
Can you explain how the Adam optimizer works?
Sure! The Adam optimizer combines the benefits of two other optimizers: AdaGrad and RMSProp. It adjusts the learning rate based on the first and second moments of the gradients.
When should I use SGD instead of Adam?
SGD is often preferred for training models with a lot of data and when you want more control over the learning rate. It can lead to better generalization in some cases.
Are there any specific use cases for RMSprop?
Yes, RMSprop is particularly effective for training recurrent neural networks and when dealing with non-stationary objectives.
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