Difference between revisions of "Loss"
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|description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools | |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools | ||
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| − | [http://www.youtube.com/results?search_query= | + | [http://www.youtube.com/results?search_query=loss+deep+learning YouTube search...] |
| − | [http://www.google.com/search?q= | + | [http://www.google.com/search?q=loss+machine+learning+ML+artificial+intelligence ...Google search] |
* [[Optimizer]] Parameter | * [[Optimizer]] Parameter | ||
| − | * [ | + | * [http://github.com/llSourcell/loss_functions_explained Loss Functions Explained | Siraj Raval] |
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| − | There are many options for | + | 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> | + | <youtube>IVVVjBSk9N0</youtube> |
| − | <youtube> | + | <youtube>78vq6kgsTa8</youtube> |
| − | <youtube> | + | <youtube>Skc8nqJirJg</youtube> |
| − | <youtube> | + | <youtube>h7iBpEHGVNc</youtube> |
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Revision as of 08:37, 31 August 2019
YouTube search... ...Google search
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. here For a list of Keras loss functions.
