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fixed typos on processing docs #1768

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Jul 29, 2020
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fixed typos on processing docs #1768

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fixed typos on processing docs
ngluna Jul 28, 2020
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Merge branch 'master' into ngl_fix_processing_typos
laurenyu Jul 28, 2020
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4 changes: 2 additions & 2 deletions doc/amazon_sagemaker_processing.rst
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Expand Up @@ -10,14 +10,14 @@ Amazon SageMaker Processing allows you to run steps for data pre- or post-proces
Background
==========

Amazon SageMaker lets developers and data scientists train and deploy machine learning models. With Amazon SageMaker Processing, you can run processing jobs on for data processing steps in your machine learning pipeline, which accept data from Amazon S3 as input, and put data into Amazon S3 as output.
Amazon SageMaker lets developers and data scientists train and deploy machine learning models. With Amazon SageMaker Processing, you can run processing jobs for data processing steps in your machine learning pipeline. Processing jobs accept data from Amazon S3 as input and store data into Amazon S3 as output.

.. image:: ./amazon_sagemaker_processing_image1.png

Setup
=====

The fastest way to run get started with Amazon SageMaker Processing is by running a Jupyter notebook. You can follow the `Getting Started with Amazon SageMaker`_ guide to start running notebooks on Amazon SageMaker.
The fastest way to get started with Amazon SageMaker Processing is by running a Jupyter notebook. You can follow the `Getting Started with Amazon SageMaker`_ guide to start running notebooks on Amazon SageMaker.

.. _Getting Started with Amazon SageMaker: https://docs.aws.amazon.com/sagemaker/latest/dg/gs.html

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