TEChopra1000 commented on a change in pull request #16500: Fixing broken links URL: https://github.com/apache/incubator-mxnet/pull/16500#discussion_r335616730
########## File path: docs/python_docs/python/tutorials/packages/gluon/loss/loss.md ########## @@ -19,8 +19,8 @@ Loss functions are used to train neural networks and to compute the difference between output and target variable. A critical component of training neural networks is the loss function. A loss function is a quantative measure of how bad the predictions of the network are when compared to ground truth labels. Given this score, a network can improve by iteratively updating its weights to minimise this loss. Some tasks use a combination of multiple loss functions, but often you'll just use one. MXNet Gluon provides a number of the most commonly used loss functions, and you'll choose certain loss functions depending on your network and task. Some common task and loss function pairs include: -- regression: [L1Loss](/api/python/docs/api/gluon/_autogen/mxnet.gluon.loss.L1Loss.html), [L2Loss](/api/python/docs/api/gluon/_autogen/mxnet.gluon.loss.L2Loss.html) -- classification: [SigmoidBinaryCrossEntropyLoss](/api/python/docs/api/gluon/_autogen/mxnet.gluon.loss.SigmoidBinaryCrossEntropyLoss.html), [SoftmaxBinaryCrossEntropyLoss](/api/python/docs/api/gluon/_autogen/mxnet.gluon.loss.SoftmaxBinaryCrossEntropyLoss.html) +- regression: [L1Loss](/api/python/docs/api/gluon/_autogen/mxnet.gluon.loss.L1Loss.html), [L2Loss](/api/python/docs/api/gluon/loss/index.html#mxnet.gluon.loss.L2Loss) Review comment: ```suggestion - regression: [L1Loss](/api/python/docs/api/gluon/loss/index.html#mxnet.gluon.loss.L1Loss), [L2Loss](/api/python/docs/api/gluon/loss/index.html#mxnet.gluon.loss.L2Loss) ``` ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
