Merge pull request #84174 from nibaccam/sklearn-hack

Sklearn | link update

Author: PRMerger14

articles/machine-learning/service/how-to-train-scikit-learn.md

@@ -130,7 +130,7 @@ For more information on compute targets, see the [what is a compute target](conc
 
 ## Create a scikit-learn estimator
 
-The [scikit-learn estimator](https://docs.microsoft.com/python/api/azureml-train-core/azureml.train.dnn.tensorflow?view=azure-ml-py) provides a simple way of launching a scikit-learn training job on a compute target. It is implemented through the [`SKLearn`](https://docs.microsoft.com/python/api/azureml-train-core/azureml.train.sklearn.sklearn?view=azure-ml-py) class, which can be used to support single-node CPU training.
+The [scikit-learn estimator](https://docs.microsoft.com/en-us/python/api/azureml-train-core/azureml.train.sklearn?view=azure-ml-py) provides a simple way of launching a scikit-learn training job on a compute target. It is implemented through the [`SKLearn`](https://docs.microsoft.com/python/api/azureml-train-core/azureml.train.sklearn.sklearn?view=azure-ml-py) class, which can be used to support single-node CPU training.
 
 If your training script needs additional pip or conda packages to run, you can have the packages installed on the resulting docker image by passing their names through the `pip_packages` and `conda_packages` arguments.