update doc with ntm algorithm

Author: yangaws

README.rst

@@ -39,7 +39,7 @@ You can install from source by cloning this repository and issuing a pip install
 
     git clone https://github.com/aws/sagemaker-python-sdk.git
     python setup.py sdist
-    pip install dist/sagemaker-1.0.3.tar.gz
+    pip install dist/sagemaker-1.0.4.tar.gz
 
 Supported Python versions
 ~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -1447,7 +1447,7 @@ Amazon SageMaker provides several built-in machine learning algorithms that you
 
 The full list of algorithms is available on the AWS website: https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html
 
-SageMaker Python SDK includes Estimator wrappers for the AWS K-means, Principal Components Analysis, Linear Learner, Factorization Machines and LDA algorithms.
+SageMaker Python SDK includes Estimator wrappers for the AWS K-means, Principal Components Analysis(PCA), Linear Learner, Factorization Machines, Latent Dirichlet Allocation(LDA) and Neural Topic Model(NTM) algorithms.
 
 Definition and usage
 ~~~~~~~~~~~~~~~~~~~~

doc/conf.py

@@ -18,7 +18,7 @@ def __getattr__(cls, name):
                 'tensorflow.python.framework', 'tensorflow_serving', 'tensorflow_serving.apis']
 sys.modules.update((mod_name, Mock()) for mod_name in MOCK_MODULES)
 
-version = '1.0.3'
+version = '1.0.4'
 project = u'sagemaker'
 
 # Add any Sphinx extension module names here, as strings. They can be extensions

doc/index.rst

@@ -49,3 +49,4 @@ Amazon provides implementations of some common machine learning algortithms opti
     sagemaker.amazon.amazon_estimator
     factorization_machines
     lda
+    ntm

doc/ntm.rst

@@ -0,0 +1,23 @@
+NTM
+--------------------
+
+The Amazon SageMaker NTM algorithm.
+
+.. autoclass:: sagemaker.NTM
+    :members:
+    :undoc-members:
+    :show-inheritance:
+    :inherited-members:
+    :exclude-members: image, num_topics, encoder_layers, epochs, encoder_layers_activation, optimizer, tolerance,
+                 num_patience_epochs, batch_norm, rescale_gradient, clip_gradient, weight_decay, learning_rate
+
+
+.. autoclass:: sagemaker.NTMModel
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. autoclass:: sagemaker.NTMPredictor
+    :members:
+    :undoc-members:
+    :show-inheritance: