Skip to content

Commit dc70fd6

Browse files
eslesar-awslaurenyu
authored andcommitted
Move overview content from main readme into sphynx project (#666)
1 parent 8b33a30 commit dc70fd6

File tree

3 files changed

+720
-13
lines changed

3 files changed

+720
-13
lines changed

CHANGELOG.rst

Lines changed: 3 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -2,13 +2,16 @@
22
CHANGELOG
33
=========
44

5+
56
1.18.4.dev
67
==========
78

89
* doc-fix: Remove incorrect parameter for EI TFS Python README
910
* feature: ``Predictor``: delete SageMaker model
1011
* feature: ``Pipeline``: delete SageMaker model
1112
* bug-fix: Estimator.attach works with training jobs without hyperparameters
13+
* doc-fix: remove duplicate content from mxnet/README.rst
14+
* doc-fix: move overview content in main README into sphynx project
1215
* bug-fix: pass accelerator_type in ``deploy`` for REST API TFS ``Model``
1316

1417
1.18.3.post1

doc/index.rst

Lines changed: 30 additions & 13 deletions
Original file line numberDiff line numberDiff line change
@@ -1,14 +1,22 @@
1+
###########################
12
Amazon SageMaker Python SDK
2-
===========================
3+
###########################
34
Amazon SageMaker Python SDK is an open source library for training and deploying machine-learned models on Amazon SageMaker.
45

56
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.
67

7-
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.
8+
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.
89

10+
********
911
Overview
10-
--------
11-
The SageMaker Python SDK consists of a few primary interfaces:
12+
********
13+
14+
.. toctree::
15+
:maxdepth: 2
16+
17+
overview
18+
19+
The SageMaker Python SDK consists of a few primary classes:
1220

1321
.. toctree::
1422
:maxdepth: 2
@@ -22,8 +30,9 @@ The SageMaker Python SDK consists of a few primary interfaces:
2230
session
2331
analytics
2432

33+
*****
2534
MXNet
26-
-----
35+
*****
2736
A managed environment for MXNet training and hosting on Amazon SageMaker
2837

2938
.. toctree::
@@ -36,62 +45,69 @@ A managed environment for MXNet training and hosting on Amazon SageMaker
3645

3746
sagemaker.mxnet
3847

48+
**********
3949
TensorFlow
40-
----------
50+
**********
4151
A managed environment for TensorFlow training and hosting on Amazon SageMaker
4252

4353
.. toctree::
4454
:maxdepth: 2
4555

4656
sagemaker.tensorflow
4757

58+
************
4859
Scikit-Learn
49-
------------
60+
************
5061
A managed enrionment for Scikit-learn training and hosting on Amazon SageMaker
5162

5263
.. toctree::
5364
:maxdepth: 2
5465

5566
sagemaker.sklearn
5667

68+
*******
5769
PyTorch
58-
-------
70+
*******
5971
A managed environment for PyTorch training and hosting on Amazon SageMaker
6072

6173
.. toctree::
6274
:maxdepth: 2
6375

6476
sagemaker.pytorch
6577

78+
*******
6679
Chainer
67-
-------
80+
*******
6881
A managed environment for Chainer training and hosting on Amazon SageMaker
6982

7083
.. toctree::
7184
:maxdepth: 2
7285

7386
sagemaker.chainer
7487

88+
**********************
7589
Reinforcement Learning
76-
----------------------
90+
**********************
7791
A managed environment for Reinforcement Learning training and hosting on Amazon SageMaker
7892

7993
.. toctree::
8094
:maxdepth: 2
8195

8296
sagemaker.rl
8397

98+
***************
8499
SparkML Serving
85-
---------------
100+
***************
86101
A managed environment for SparkML hosting on Amazon SageMaker
87102

88103
.. toctree::
89104
:maxdepth: 2
90105

91106
sagemaker.sparkml
92107

108+
********************************
93109
SageMaker First-Party Algorithms
94-
--------------------------------
110+
********************************
95111
Amazon provides implementations of some common machine learning algortithms optimized for GPU architecture and massive datasets.
96112

97113
.. toctree::
@@ -109,8 +125,9 @@ Amazon provides implementations of some common machine learning algortithms opti
109125
pca
110126
randomcutforest
111127

128+
*********
112129
Workflows
113-
---------
130+
*********
114131
SageMaker APIs to export configurations for creating and managing Airflow workflows.
115132

116133
.. toctree::

0 commit comments

Comments
 (0)