Merge pull request #3491 from sdgilley/sdg-freshness

fix typo

Author: prmerger-automator[bot]

articles/machine-learning/v1/how-to-set-up-training-targets.md

@@ -206,7 +206,7 @@ See these notebooks for examples of configuring jobs for various training scenar
 
  * **ModuleErrors (No module named)**:  If . you're running into ModuleErrors while submitting experiments in Azure Machine Learning, the training script is expecting a package to be installed but it isn't added. Once you provide the package name, Azure Machine Learning installs the package in the environment used for your training job.
 
-    If . you're using Estimators to submit experiments, you can specify a package name via `pip_packages` or `conda_packages` parameter in the estimator based on from which source you want to install the package. You can also specify a yml file with all your dependencies using `conda_dependencies_file`or list all your pip requirements in a txt file using `pip_requirements_file` parameter. If you have your own Azure Machine Learning Environment object that you want to override the default image used by the estimator, you can specify that environment via the `environment` parameter of the estimator constructor.
+    If you're using Estimators to submit experiments, you can specify a package name via `pip_packages` or `conda_packages` parameter in the estimator based on from which source you want to install the package. You can also specify a yml file with all your dependencies using `conda_dependencies_file`or list all your pip requirements in a txt file using `pip_requirements_file` parameter. If you have your own Azure Machine Learning Environment object that you want to override the default image used by the estimator, you can specify that environment via the `environment` parameter of the estimator constructor.
 
     Azure Machine Learning maintained docker images and their contents can be seen in [Azure Machine Learning Containers](https://github.com/Azure/AzureML-Containers).
     Framework-specific dependencies  are listed in the respective framework documentation: