Updated: README with note on tensorflow and mxnet spinup times

Author: djarpin

README.md

@@ -51,13 +51,17 @@ These examples that showcase unique functionality available in Amazon SageMaker.
 
 These examples focus on the Amazon SageMaker Python SDK which allows you to write idiomatic TensorFlow or MXNet and then train or host in pre-built containers.
 
+_Note, the first time these examples are loaded, they can take up to several minutes for the kernel to begin.  The circle in the upper right hand corner of the notebook will change from filled-in to empty when the kernel is ready._
+
 - [cifar 10 with MXNet Gluon](sagemaker-python-sdk/mxnet_gluon_cifar10)
 - [MNIST with MXNet Gluon](sagemaker-python-sdk/mxnet_gluon_mnist)
 - [MNIST with MXNet](sagemaker-python-sdk/mxnet_mnist)
+- [Sentiment Analysis with MXNet Gluon](sagemaker-python-sdk/mxnet_gluon_sentiment)
 - [TensorFlow Neural Networks with Layers](sagemaker-python-sdk/tensorflow_abalone_age_predictor_using_layers)
-- [TensorFlow Networks with Keras](sagemaker-python-sdk/tensorflow_abalone_age_predictor_keras)
+- [TensorFlow Networks with Keras](sagemaker-python-sdk/tensorflow_abalone_age_predictor_using_keras)
 - [Introduction to Estimators in TensorFlow](sagemaker-python-sdk/tensorflow_iris_dnn_classifier_using_estimators)
 - [TensorFlow and TensorBoard](sagemaker-python-sdk/tensorflow_resnet_cifar10_with_tensorboard)
+- [Distributed TensorFlow)(sagemaker-python-sdk/tensorflow_distributed_mnist)
 
 ### Under Development