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6 changes: 6 additions & 0 deletions CHANGELOG.rst
Original file line number Diff line number Diff line change
Expand Up @@ -2,14 +2,20 @@
CHANGELOG
=========


1.18.4.dev
==========

* doc-fix: Remove incorrect parameter for EI TFS Python README
* feature: ``Predictor``: delete SageMaker model
* feature: ``Pipeline``: delete SageMaker model
* bug-fix: Estimator.attach works with training jobs without hyperparameters
<<<<<<< HEAD
* doc-fix: remove duplicate content from mxnet/README.rst
* doc-fix: move overview content in main README into sphynx project
=======
* bug-fix: pass accelerator_type in ``deploy`` for REST API TFS ``Model``
>>>>>>> 8b33a305110997e18b1f2f2a37b2d3cdd98b2f91
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bad merge?

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Sorry...should be fixed now.


1.18.3.post1
============
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43 changes: 30 additions & 13 deletions doc/index.rst
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###########################
Amazon SageMaker Python SDK
===========================
###########################
Amazon SageMaker Python SDK is an open source library for training and deploying machine-learned models on Amazon SageMaker.

With the SDK, you can train and deploy models using popular deep learning frameworks, algorithms provided by Amazon, or your own algorithms built into SageMaker-compatible Docker images.

Here you'll find API docs for SageMaker Python SDK. The project homepage is in Github: https://github.com/aws/sagemaker-python-sdk, where you can find the SDK source, installation instructions and a general overview of the library.
Here you'll find an overview and API documentation for SageMaker Python SDK. The project homepage is in Github: https://github.com/aws/sagemaker-python-sdk, where you can find the SDK source and installation instructions for the library.

********
Overview
--------
The SageMaker Python SDK consists of a few primary interfaces:
********

.. toctree::
:maxdepth: 2

overview

The SageMaker Python SDK consists of a few primary classes:

.. toctree::
:maxdepth: 2
Expand All @@ -22,8 +30,9 @@ The SageMaker Python SDK consists of a few primary interfaces:
session
analytics

*****
MXNet
-----
*****
A managed environment for MXNet training and hosting on Amazon SageMaker

.. toctree::
Expand All @@ -36,62 +45,69 @@ A managed environment for MXNet training and hosting on Amazon SageMaker

sagemaker.mxnet

**********
TensorFlow
----------
**********
A managed environment for TensorFlow training and hosting on Amazon SageMaker

.. toctree::
:maxdepth: 2

sagemaker.tensorflow

************
Scikit-Learn
------------
************
A managed enrionment for Scikit-learn training and hosting on Amazon SageMaker

.. toctree::
:maxdepth: 2

sagemaker.sklearn

*******
PyTorch
-------
*******
A managed environment for PyTorch training and hosting on Amazon SageMaker

.. toctree::
:maxdepth: 2

sagemaker.pytorch

*******
Chainer
-------
*******
A managed environment for Chainer training and hosting on Amazon SageMaker

.. toctree::
:maxdepth: 2

sagemaker.chainer

**********************
Reinforcement Learning
----------------------
**********************
A managed environment for Reinforcement Learning training and hosting on Amazon SageMaker

.. toctree::
:maxdepth: 2

sagemaker.rl

***************
SparkML Serving
---------------
***************
A managed environment for SparkML hosting on Amazon SageMaker

.. toctree::
:maxdepth: 2

sagemaker.sparkml

********************************
SageMaker First-Party Algorithms
--------------------------------
********************************
Amazon provides implementations of some common machine learning algortithms optimized for GPU architecture and massive datasets.

.. toctree::
Expand All @@ -109,8 +125,9 @@ Amazon provides implementations of some common machine learning algortithms opti
pca
randomcutforest

*********
Workflows
---------
*********
SageMaker APIs to export configurations for creating and managing Airflow workflows.

.. toctree::
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