Reword hptuning explanation
"source": [
"### Hyperparameter tuning\n",
"\n",
- "If you want to perform Hyperparameter tuning with TF-Keras you can use the attached file: `hptuning_config.yaml`\n",
- "This file will use batch-size and learning rate to maximize the best accuracy. \n",
- "More information on Hyperparameter tuning [here](https://cloud.google.com/ml-engine/docs/tensorflow/hyperparameter-tuning-overview). In this example we use the Tensorboard callback which uses `tf.summary.FileWriter.add_summary` under the hood which is being used by AI platform to monitor and report the metrics."
+ "You can optionally perform hyperparameter tuning by using the included\n",
+ "`hptuning_config.yaml` configuration file. This file tells AI Platform to tune the batch size and learning rate for training over multiple trials to maximize accuracy.\n",
+ "\n",
+ "In this example, the training code uses a [Tensorboard\n",
+ "callback](https://www.tensorflow.org/api_docs/python/tf/keras/callbacks/TensorBoard),\n",
+ "which [creates TensorFlow `Summary`\n",
+ "`Event`s](https://www.tensorflow.org/api_docs/python/tf/summary/FileWriter#add_summary)\n",
+ "during training. AI Platform uses these events to track the metric you want to\n",
+ "optimize. Learn more about [hyperparmeter tuning in\n",
+ "AI Platform Training](https://cloud.google.com/ml-engine/docs/tensorflow/hyperparameter-tuning-overview)."
]
},
{
