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Scenario: The Tivan Group, a prestigious and influential organization in the galactic community, is known for its immense wealth and contributions to the galaxy. Founded by the infamous Collector, Taneleer Tivan, the group is integrating Microsoft Azure into its operations. The IT team has been actively developing an Azure Machine Learning workspace, creating the following Azure resource groups and resources: ml_resources: An Azure Machine Learning workspace named amlworkspace An Azure Storage account named amlworkspace_tivian An Application Insights instance named amlworkspace_taneleer An Azure Key Vault named amlworkspace_thanos An Azure Container Registry named amlworkspace_gamora general_compute: A virtual machine named mlvm with the following configuration: Operating system: Ubuntu Linux Software installed: Python 3.6 and Jupyter Notebooks Size: NC6 (6 vCPUs, 1 vGPU, 56 GB RAM) Additionally, the IT department has created an Azure Kubernetes Service (AKS)-based inference compute target named aks-cluster in the Azure Machine Learning workspace. As the expert consultant, you are equipped with a Microsoft Surface Book that includes a GPU, with Python 3.6 and Visual Studio Code installed. Your task is to train a deep neural network (DNN) model while logging loss and accuracy metrics. To accomplish this, you install the Azure ML SDK on your Surface Book, run Python code to connect to the workspace, and execute the training script as an experiment on local compute. Will this solution function as expected?