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| author |  Michael Case <mikecase@google.com> | 2018-02-07 14:36:00 -0800 |
|---|---|---|
| committer |  TensorFlower Gardener <gardener@tensorflow.org> | 2018-02-07 14:39:49 -0800 |
| commit | d90054e7c0f41f4bab81df0548577a73b939a87a (patch) | |
| tree | a15aea686a9d3f305e316d2a6ada0859ad8170d1 /tensorflow/docs_src/get_started/premade_estimators.md | |
| parent | 8461760f9f6cde8ed97507484d2a879140141032 (diff) | |
Merge changes from github.
PiperOrigin-RevId: 184897758
Diffstat (limited to 'tensorflow/docs_src/get_started/premade_estimators.md')
| -rw-r--r-- | tensorflow/docs_src/get_started/premade_estimators.md | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/tensorflow/docs_src/get_started/premade_estimators.md b/tensorflow/docs_src/get_started/premade_estimators.md index 45850a8996..4f01f997c3 100644 --- a/tensorflow/docs_src/get_started/premade_estimators.md +++ b/tensorflow/docs_src/get_started/premade_estimators.md @@ -372,7 +372,7 @@ Test set accuracy: 0.967 We now have a trained model that produces good evaluation results. We can now use the trained model to predict the species of an Iris flower -based on some unlabeled measurments. As with training and evaluation, we make +based on some unlabeled measurements. As with training and evaluation, we make predictions using a single function call: ```python |