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Merge pull request #50695 from sherzyang/main
Update ML module with fixes.
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### YamlMime:ModuleUnit
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uid: learn.wwl.design-machine-learning-model-training-solution.introduction
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title: Introduction
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metadata:
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title: Introduction
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description: Introduction
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author: wwlpublish
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ms.author: madiepev
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ms.date: 01/20/2025
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ms.topic: unit
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durationInMinutes: 3
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content: |
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[!include[](includes/1-introduction.md)]
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### YamlMime:ModuleUnit
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uid: learn.wwl.design-machine-learning-model-training-solution.introduction
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title: Introduction
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metadata:
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title: Introduction
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description: Introduction
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author: wwlpublish
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ms.author: madiepev
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ms.date: 05/28/2025
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[!include[](includes/1-introduction.md)]
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### YamlMime:ModuleUnit
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uid: learn.wwl.design-machine-learning-model-training-solution.identify-tasks
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title: Define the problem
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metadata:
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title: Define the problem
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description: Define the problem
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author: wwlpublish
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ms.author: madiepev
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ms.date: 01/20/2025
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ms.topic: unit
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durationInMinutes: 4
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content: |
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[!include[](includes/2-identify-tasks.md)]
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### YamlMime:ModuleUnit
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uid: learn.wwl.design-machine-learning-model-training-solution.identify-tasks
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title: Define the problem
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metadata:
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title: Define the problem
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description: Define the problem
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author: wwlpublish
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ms.author: madiepev
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ms.date: 05/28/2025
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ms.topic: unit
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[!include[](includes/2-identify-tasks.md)]
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### YamlMime:ModuleUnit
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uid: learn.wwl.design-machine-learning-model-training-solution.prepare-data
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title: Get and prepare data
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metadata:
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title: Get and prepare data
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description: Get and prepare data
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author: wwlpublish
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ms.author: madiepev
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ms.date: 01/20/2025
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ms.topic: unit
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ms.collection:
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labModal: false
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durationInMinutes: 5
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content: |
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[!include[](includes/2a-prepare-data.md)]
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### YamlMime:ModuleUnit
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uid: learn.wwl.design-machine-learning-model-training-solution.prepare-data
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title: Get and prepare data
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metadata:
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title: Get and prepare data
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description: Get and prepare data
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author: wwlpublish
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ms.author: madiepev
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ms.date: 05/28/2025
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ms.topic: unit
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ms.collection:
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- wwl-ai-copilot
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azureSandbox: false
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durationInMinutes: 5
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[!include[](includes/2a-prepare-data.md)]
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### YamlMime:ModuleUnit
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uid: learn.wwl.design-machine-learning-model-training-solution.choose-service-train
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title: Train the model
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metadata:
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title: Train the model
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description: Train the model
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author: wwlpublish
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ms.author: madiepev
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ms.date: 01/20/2025
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ms.topic: unit
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ms.collection:
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durationInMinutes: 7
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content: |
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[!include[](includes/3-choose-service-train.md)]
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### YamlMime:ModuleUnit
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uid: learn.wwl.design-machine-learning-model-training-solution.choose-service-train
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title: Train the model
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metadata:
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title: Train the model
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description: Train the model
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author: wwlpublish
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ms.author: madiepev
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ms.date: 05/28/2025
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ms.topic: unit
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[!include[](includes/3-choose-service-train.md)]
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### YamlMime:ModuleUnit
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uid: learn.wwl.design-machine-learning-model-training-solution.use-automated-machine-learning
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title: Use Azure Machine Learning studio
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metadata:
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title: Use Azure Machine Learning studio
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description: Use Azure Machine Learning studio
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author: wwlpublish
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ms.author: sheryang
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ms.date: 05/28/2025
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ms.topic: unit
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azureSandbox: false
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durationInMinutes: 3
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content: |
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[!include[](includes/3b-use-automated-machine-learning.md)]
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### YamlMime:ModuleUnit
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uid: learn.wwl.design-machine-learning-model-training-solution.decide-between-compute-options
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title: Integrate a model
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metadata:
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title: Integrate a model
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description: Integrate a model
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author: wwlpublish
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ms.author: madiepev
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ms.topic: unit
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durationInMinutes: 7
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content: |
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[!include[](includes/4-decide-between-compute-options.md)]
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### YamlMime:ModuleUnit
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uid: learn.wwl.design-machine-learning-model-training-solution.decide-between-compute-options
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title: Integrate a model
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metadata:
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title: Integrate a model
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description: Integrate a model
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author: wwlpublish
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ms.author: madiepev
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ms.date: 05/28/2025
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ms.topic: unit
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ms.collection:
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content: |
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[!include[](includes/4-decide-between-compute-options.md)]
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### YamlMime:ModuleUnit
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uid: learn.wwl.design-machine-learning-model-training-solution.exercise
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title: Monitor the model
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metadata:
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title: Monitor the model
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description: Monitor the model
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author: wwlpublish
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ms.author: madiepev
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ms.date: 01/20/2025
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ms.topic: unit
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labModal: false
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durationInMinutes: 6
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content: |
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[!include[](includes/5-exercise.md)]
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### YamlMime:ModuleUnit
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uid: learn.wwl.design-machine-learning-model-training-solution.exercise
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title: Exercise - Explore Automated Machine Learning in Azure Machine Learning
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metadata:
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title: Exercise - Explore Automated Machine Learning in Azure Machine Learning
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description: In this exercise you'll use the automated machine learning feature in Azure Machine Learning to train and evaluate a machine learning model. You'll then deploy and test the trained model.
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author: wwlpublish
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ms.author: sheryang
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ms.date: 05/28/2025
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ms.topic: unit
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content: |
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[!include[](includes/5-exercise.md)]
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### YamlMime:ModuleUnit
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uid: learn.wwl.design-machine-learning-model-training-solution.knowledge-check
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title: Module assessment
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metadata:
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title: Module assessment
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description: Knowledge check
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author: wwlpublish
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ms.author: madiepev
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ms.date: 01/20/2025
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ms.topic: unit
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ms.collection:
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azureSandbox: false
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labModal: false
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durationInMinutes: 3
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content: |
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[!include[](includes/6-knowledge-check.md)]
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quiz:
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questions:
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- content: "Which compute would you recommend to train the model?"
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choices:
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- content: "Spark cluster"
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isCorrect: false
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explanation: "Incorrect. Since the data scientists aren't familiar with Spark, it's not the preferred solution right now."
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- content: "CPU"
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isCorrect: true
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explanation: "Correct. CPU compute is the best option for training the model. There can be a need for GPU or Spark when model training takes too long, but for now it's best to start with CPUs."
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- content: "GPU"
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isCorrect: false
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explanation: "Incorrect. There's no indication yet that GPUs are needed to train the model, and using GPUs over CPUs now, only incurs unnecessary extra costs."
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- content: "What type of predictions does the mobile application need to generate?"
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choices:
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- content: "Real-time predictions"
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isCorrect: true
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explanation: "Correct. There's a need for immediate predictions for individual patients."
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- content: "Batch predictions"
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isCorrect: false
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explanation: "Incorrect. Batch predictions would take too long. We need immediate predictions."
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- content: "Local predictions"
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isCorrect: false
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explanation: "Incorrect. There's a need for immediate predictions for individual patients so we need real-time predictions."
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### YamlMime:ModuleUnit
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uid: learn.wwl.design-machine-learning-model-training-solution.knowledge-check
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title: Module assessment
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metadata:
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title: Module assessment
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description: "Knowledge check"
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ms.date: 05/28/2025
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author: wwlpublish
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ms.author: sheryang
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ms.topic: unit
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ms.custom:
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- N/A
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durationInMinutes: 3
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quiz:
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questions:
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- content: "What does Automated machine learning in Azure Machine Learning enable you to do?"
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choices:
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- content: "Automatically deploy new versions of a model as they're trained"
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isCorrect: false
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explanation: "Incorrect. Automated machine learning does not automatically deploy models."
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- content: "Automatically provision Azure Machine Learning workspaces for new data scientists in an organization"
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isCorrect: false
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explanation: "Incorrect. Automated machine learning does not automate workspace provisioning."
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- content: "Automatically run multiple training jobs using different algorithms and parameters to find the best model"
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isCorrect: true
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explanation: "Correct. Automated machine learning runs multiple training jobs, varying algorithms and parameters, to find the best model for your data."
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- content: "Which of the following factors should you consider when choosing a service to train a machine learning model?"
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choices:
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- content: "The number of users in your organization."
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isCorrect: false
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explanation: "Incorrect."
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- content: "How much time you want to invest in model training."
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isCorrect: true
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explanation: "Correct."
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- content: "The approximate number of predictions the model needs to make in a month."
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isCorrect: false
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explanation: "Incorrect."
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- content: "What is a key feature of Azure Machine Learning that supports end-to-end machine learning workflows?"
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choices:
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- content: "It provides ready-to-use models for image classification."
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isCorrect: false
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explanation: "Incorrect."
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- content: "It requires integration with Microsoft Fabric to deploy models."
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isCorrect: false
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explanation: "Incorrect."
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- content: " It offers centralized dataset management and automated machine learning."
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isCorrect: true
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explanation: "Correct."
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### YamlMime:ModuleUnit
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uid: learn.wwl.design-machine-learning-model-training-solution.summary
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title: Summary
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metadata:
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title: Summary
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description: Summary
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author: wwlpublish
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ms.author: madiepev
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ms.date: 01/20/2025
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[!include[](includes/7-summary.md)]
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### YamlMime:ModuleUnit
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uid: learn.wwl.design-machine-learning-model-training-solution.summary
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title: Summary
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metadata:
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title: Summary
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description: Summary
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author: wwlpublish
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ms.author: sheryang
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[!include[](includes/7-summary.md)]
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learn-pr/wwl-data-ai/design-machine-learning-model-training-solution/includes/1-introduction.md

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Thoughtfully designed machine learning solutions form the foundation of today's AI applications. From predictive analytics to personalized recommendations and beyond, machine learning solutions support the latest technological advances in society by using existing data to produce new insights.
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As a data scientist, you can make decisions to tackle machine learning problems in different ways. The decisions you make affect the cost, speed, quality, and longevity of the solution.
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Data scientists make decisions to tackle machine learning problems in different ways. The decisions they make affect the cost, speed, quality, and longevity of the solution.
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In this module, you learn how to design an end-to-end machine learning solution with Microsoft Azure that can be used in an enterprise setting. Using the following six steps as a framework, we explore how to plan, train, deploy, and monitor machine learning solutions.
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1. **Monitor the model**: Track the model's performance.
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> [!Note]
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> The diagram is a simplified representation of the machine learning process. Typically, the process is iterative and continuous. For example, when monitoring the model you may decide to go back and retrain the model.
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> The diagram is a simplified representation of the machine learning process. Typically, the process is iterative and continuous. For example, when monitoring the model you may decide to go back and retrain the model.
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Next, let's look at how we can get started on a machine learning solution by defining the problem.

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