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Add tensorboard docs #123

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Expand Up @@ -119,6 +119,18 @@ def train_dogs_vs_cats(exp): # Get Experiment object as argument to function.
model.fit()
exp.metric(model.accuracy())
```

## Tensorboard auto-instrumentation.
If you use Tensorboard for monitoring, Hyperdash can monitor the same `tfevents` files. Simply point the Hyperdash SDK to your log directory. For example if you start tensorboard in Terminal like this:
```bash
tensorboard --logdir=/tmp/tensorflow_logs
```
You would run in a seperate terminal tab:
```bash
hd tensorboard -n ModelNameHere --logdir=/tmp/tensorflow_logs
```
Then Hyperdash will automatically categorize all future tensorflow runs in the same directory under the same model name. You'll even get push notifications and real-time metrics!

## API Keys
### Storage

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