aaronmarkham commented on a change in pull request #15065: [MXNET] Updated 
http://data.dmlc.ml/ links to http://data.mxnet.io/
URL: https://github.com/apache/incubator-mxnet/pull/15065#discussion_r287539157
 
 

 ##########
 File path: example/rcnn/README.md
 ##########
 @@ -43,8 +43,8 @@ Make a directory `data` and follow `py-faster-rcnn` for data 
preparation instruc
 * [MSCOCO](http://mscoco.org/dataset/) should be in `data/coco` containing 
`train2017`, `val2017` and `annotations/instances_train2017.json`, 
`annotations/instances_val2017.json`.
 
 ### Download pretrained ImageNet models
-* [VGG16](http://www.robots.ox.ac.uk/~vgg/research/very_deep/) should be at 
`model/vgg16-0000.params` from [MXNet model 
zoo](http://data.dmlc.ml/models/imagenet/vgg/).
-* [ResNet](https://github.com/tornadomeet/ResNet) should be at 
`model/resnet-101-0000.params` from [MXNet model 
zoo](http://data.dmlc.ml/models/imagenet/resnet/).
+* [VGG16](http://www.robots.ox.ac.uk/~vgg/research/very_deep/) should be at 
`model/vgg16-0000.params` from [MXNet model 
zoo](http://data.mxnet.io/models/imagenet/vgg/).
 
 Review comment:
   Ok, use the AWS CLI to browse around:
   ```
   aws s3 ls s3://data.mxnet.io
   aws s3 ls s3://data.mxnet.io/mxnet/models/imagenet/vgg/
   ```
   Then you should be able to figure out the links that way.

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