[GitHub] [beam] rszper commented on a diff in pull request #24125: Editorial review of the ML notebooks.

[GitBox <gi...@apache.org>]

rszper commented on code in PR #24125:
URL: https://github.com/apache/beam/pull/24125#discussion_r1022130309


##########
examples/notebooks/beam-ml/custom_remote_inference.ipynb:
##########
@@ -34,13 +34,17 @@
         "id": "0UGzzndTBPWQ"
       },
       "source": [
-        "# Remote inference in Beam\n",
+        "# Remote inference in Apache Beam\n",
         "\n",
-        "The prefered way of running inference in Beam is by using the [RunInference API](https://beam.apache.org/documentation/sdks/python-machine-learning/). The RunInference API enables you to run your models as part of your pipeline in a way that is optimized for machine learning inference. It supports features such as batching, so that you do not need to take care of it yourself. For more info on the RunInference API you can check out the [RunInference notebook](https://github.com/apache/beam/blob/master/examples/notebooks/beam-ml/run_inference_pytorch_tensorflow_sklearn.ipynb), which demonstrates how you can implement model inference in pytorch, scikit-learn and tensorflow.\n",
+        "The prefered way to run inference in Apache Beam is by using the [RunInference API](https://beam.apache.org/documentation/sdks/python-machine-learning/). \n",
+        "The RunInference API enables you to run your models as part of your pipeline in a way that is optimized for machine learning inference. \n",
+        "To reduce the number of steps that you need to take, RunInference supports features like batching. For more infomation about the RunInference API, review the [RunInference notebook](https://github.com/apache/beam/blob/master/examples/notebooks/beam-ml/run_inference_pytorch_tensorflow_sklearn.ipynb), \n",

Review Comment:
   I also find this notebook confusing. I agree about the link. Will fix.



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