Difference between revisions of "Loss"
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* [http://github.com/llSourcell/loss_functions_explained Loss Functions Explained | Siraj Raval] | * [http://github.com/llSourcell/loss_functions_explained Loss Functions Explained | Siraj Raval] | ||
| − | There are many options for loss in Tensorflow (Keras). The actual optimized objective is the mean of the output array across all datapoints. Loss is one of the two parameters required to compile a model. [http://keras.io/losses/Click here For a list of Keras loss functions.] | + | There are many options for loss in Tensorflow (Keras). The actual optimized objective is the mean of the output array across all datapoints. Loss is one of the two parameters required to compile a model. [http://keras.io/losses/ Click here For a list of Keras loss functions.] |
<youtube>IVVVjBSk9N0</youtube> | <youtube>IVVVjBSk9N0</youtube> | ||
Revision as of 08:41, 31 August 2019
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There are many options for loss in Tensorflow (Keras). The actual optimized objective is the mean of the output array across all datapoints. Loss is one of the two parameters required to compile a model. Click here For a list of Keras loss functions.
