Update product name mentions in Keras notebook
There were a few iterations of "Cloud ML Engine" that I missed before since they were at string borders. (It's possible there are more cases like this in other notebooks. I'll try to look for those soon too.)
"implementation of this API.\n",
"\n",
"The first two parts of the tutorial walk through training a model on Cloud\n",
- "AI Platform using prewritten Keras code, deploying the trained model to Cloud ML\n",
- "Engine, and serving online predictions from the deployed model.\n",
+ "AI Platform using prewritten Keras code, deploying the trained model to\n",
+ "AI Platform, and serving online predictions from the deployed model.\n",
"\n",
"The last part of the tutorial digs into the training code used for this model and ensuring it's compatible with AI Platform. To learn more about building\n",
"machine learning models in Keras more generally, read [TensorFlow's Keras\n",
"source": [
"## Before you begin\n",
"\n",
- "You must do several things before you can train and deploy a model in Cloud ML\n",
- "Engine:\n",
+ "You must do several things before you can train and deploy a model in\n",
+ "AI Platform:\n",
"\n",
"* Set up your local development environment.\n",
"* Set up a GCP project with billing and the necessary\n",
"[TensorFlow SavedModel\n",
"directory](https://www.tensorflow.org/guide/saved_model#structure_of_a_savedmodel_directory)\n",
"to your Cloud Storage bucket. AI Platform uses this directory to create a\n",
- "model version. Learn more about [SavedModel and Cloud ML\n",
- "Engine](https://cloud.google.com/ml-engine/docs/tensorflow/deploying-models).\n",
+ "model version. Learn more about [SavedModel and\n",
+ "AI Platform](https://cloud.google.com/ml-engine/docs/tensorflow/deploying-models).\n",
"\n",
"You may be able to find the path to this directory in your training job's logs.\n",
"Look for a line like:\n",
"source": [
"You may export a SavedModel directory to your local filesystem or to Cloud\n",
"Storage, as long as you have the necessary permissions. In your current\n",
- "environment, you granted access to Cloud Storage by authenticating your GCP account and setting the `GOOGLE_APPLICATION_CREDENTIALS` environment variable. Cloud ML\n",
- "Engine training jobs can also export directly to Cloud Storage, because Cloud ML\n",
- "Engine service accounts [have access to Cloud Storage buckets in their own\n",
+ "environment, you granted access to Cloud Storage by authenticating your GCP account and setting the `GOOGLE_APPLICATION_CREDENTIALS` environment variable.\n",
+ "AI Platform training jobs can also export directly to Cloud Storage, because\n",
+ "AI Platform service accounts [have access to Cloud Storage buckets in their own\n",
"project](https://cloud.google.com/ml-engine/docs/tensorflow/working-with-cloud-storage).\n",
"\n",
"Try exporting directly to Cloud Storage:"
