fixing blockers

Author: Larry Franks

articles/machine-learning/how-to-train-tensorflow.md

@@ -134,7 +134,7 @@ In the training script `tf_mnist.py`, we create a simple deep neural network (DN
 - Two hidden layers. The first hidden layer has 300 neurons and the second hidden layer has 100 neurons; and
 - An output layer with 10 neurons. Each neuron represents a targeted label from 0 to 9.
 
-:::image type="content" source="media/how-to-train-tensorflow/neural_network.png" alt-text="Diagram showing a deep neural network with 784 neurons at the input layer, two hidden layers, and 10 neurons at the output layer.":::
+:::image type="content" source="media/how-to-train-tensorflow/neural-network.png" alt-text="Diagram showing a deep neural network with 784 neurons at the input layer, two hidden layers, and 10 neurons at the output layer.":::
 
 ### Build the training job
 

articles/machine-learning/media/how-to-train-tensorflow/neural_network.png renamed to articles/machine-learning/media/how-to-train-tensorflow/neural-network.png

@@ -81,7 +81,7 @@ The example code in this article assumes that you have already created a compute
 ## Create an environment
 Azure Machine Learning [environments](../concept-environments.md) are an encapsulation of the environment where your machine learning training happens. They specify the Python packages, Docker image, environment variables, and software settings around your training and scoring scripts. They also specify runtimes (Python, Spark, or Docker).
 
-You can either define your own environment, or use an Azure ML curated environment. [Curated environments](../how-to-use-environments.md#use-a-curated-environment) are predefined environments that are available in your workspace by default. These environments are backed by cached Docker images which reduces the job preparation cost. See [Azure Machine Learning Curated Environments](../resource-curated-environments.md) for the full list of available curated environments.
+You can either define your own environment, or use an Azure ML curated environment. [Curated environments](../how-to-use-environments.md#use-a-curated-environment) are predefined environments that are available in your workspace by default. These environments are backed by cached Docker images which reduce the job preparation cost. See [Azure Machine Learning Curated Environments](../resource-curated-environments.md) for the full list of available curated environments.
 
 For a remote compute target, you can use one of these popular curated environments to start with: