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Merge pull request #17057 from deroneriksson/low_level_intro_typos

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Fix typos in low-level introduction documentation
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Martin Wicke 2018-02-15 17:36:02 -08:00 committed by GitHub
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tensorflow/docs_src/programmers_guide/low_level_intro.md
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@ -295,7 +295,7 @@ the same input. @{tf.layers$Layers} are the preferred way to add trainable
parameters to a graph. parameters to a graph.
Layers package together both the variables and the operations that act Layers package together both the variables and the operations that act
on them, . For example a on them. For example a
[densely-connected layer](https://developers.google.com/machine-learning/glossary/#fully_connected_layer) [densely-connected layer](https://developers.google.com/machine-learning/glossary/#fully_connected_layer)
performs a weighted sum across all inputs performs a weighted sum across all inputs
for each output and applies an optional for each output and applies an optional
@ -478,7 +478,7 @@ good. Here's what we got; your own output will almost certainly differ:
[ 0.10527515]] [ 0.10527515]]
``` ```
### loss ### Loss
To optimize a model, you first need to define the loss. We'll use the mean To optimize a model, you first need to define the loss. We'll use the mean
square error, a standard loss for regression problems. square error, a standard loss for regression problems.