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| author |  Nicholas Nadeau, P.Eng., AVS <nnadeau@users.noreply.github.com> | 2018-05-03 13:47:06 -0400 |
|---|---|---|
| committer |  Shanqing Cai <cais@google.com> | 2018-05-03 13:47:06 -0400 |
| commit | 487fa7b1a48c151362ab1b16cdda6bbc78f5d6dc (patch) | |
| tree | 938a76a47b46d102f4833677db475aaa99e936d1 /tensorflow/docs_src/mobile | |
| parent | 4984a60e7147edef532ca1b15050471e81e45841 (diff) | |
Fixed Typos (#18806)
* fixed typos
Diffstat (limited to 'tensorflow/docs_src/mobile')
| -rw-r--r-- | tensorflow/docs_src/mobile/mobile_intro.md | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/tensorflow/docs_src/mobile/mobile_intro.md b/tensorflow/docs_src/mobile/mobile_intro.md index 69b63ae7d2..39dda0b45f 100644 --- a/tensorflow/docs_src/mobile/mobile_intro.md +++ b/tensorflow/docs_src/mobile/mobile_intro.md @@ -212,7 +212,7 @@ handle the task then it will be difficult to train a computer to do better. After you’ve solved any fundamental issues with your use case, you need to create a labeled dataset to define what problem you’re trying to solve. This -step is extremely important, moreso than picking which model to use. You want it +step is extremely important, more than picking which model to use. You want it to be as representative as possible of your actual use case, since the model will only be effective at the task you teach it. It’s also worth investing in tools to make labeling the data as efficient and accurate as possible. For |