[GitHub] [incubator-mxnet] ChaiBapchya commented on a change in pull request #16764: Link fixes4

[GitBox <gi...@apache.org>]

ChaiBapchya commented on a change in pull request #16764:
URL: https://github.com/apache/incubator-mxnet/pull/16764#discussion_r442972965



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File path: docs/python_docs/python/tutorials/getting-started/gluon_from_experiment_to_deployment.md
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@@ -267,8 +267,7 @@ finetune_net.export("flower-recognition", epoch=epochs)
 MXNet provides various useful tools and interfaces for deploying your model for inference. For example, you can use [MXNet Model Server](https://github.com/awslabs/mxnet-model-server) to start a service and host your trained model easily.
 Besides that, you can also use MXNet's different language APIs to integrate your model with your existing service. We provide [Python](/api/python.html),    [Java](/api/java.html), [Scala](/api/scala.html), and [C++](/api/cpp) APIs.
 
-Here we will briefly introduce how to run inference using Module API in Python. There is more detailed explanation available in the [Predict Image Tutorial](https://mxnet.apache.org/tutorials/python/predict_image.html).
-In general, prediction consists of the following steps:
+Here we will briefly introduce how to run inference using Module API in Python. In general, prediction consists of the following steps:

Review comment:
       Do you want to add it back? or the image-classification shouldn't exist anymore? What's the solution for that issue?




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