Skip to content

Commit 23dc043

Browse files
madiepevmadiepev
committed
new module
1 parent 8943d84 commit 23dc043

38 files changed

Lines changed: 908 additions & 0 deletions

‎learn-pr/wwl-azure/experiment-azure-machine-learning/1-introduction.yml‎

Lines changed: 16 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,16 @@
1+
### YamlMime:ModuleUnit
2+
uid: learn.wwl.experiment-azure-machine-learning.introduction
3+
title: Introduction
4+
metadata:
5+
title: Introduction
6+
description: Learn how to find the best model with automated machine learning (AutoML) and by experimenting in notebooks in Azure Machine Learning.
7+
author: wwlpublish
8+
ms.author: madiepev
9+
ms.date: 03/11/2026
10+
ms.topic: unit
11+
ms.collection:
12+
- wwl-ai-copilot
13+
ms.custom: devx-track-python
14+
durationInMinutes: 2
15+
content: |
16+
[!include[](includes/1-introduction.md)]

‎learn-pr/wwl-azure/experiment-azure-machine-learning/2-preprocess-data-configure-featurization.yml‎

Lines changed: 16 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,16 @@
1+
### YamlMime:ModuleUnit
2+
uid: learn.wwl.experiment-azure-machine-learning.preprocess-data-configure-featurization
3+
title: Preprocess data and configure featurization
4+
metadata:
5+
title: Preprocess data and configure featurization
6+
description: Learn how to configure automated machine learning to preprocess data and perform featurization with the Python SDK (v2) for Azure Machine Learning.
7+
author: wwlpublish
8+
ms.author: madiepev
9+
ms.date: 03/11/2026
10+
ms.topic: unit
11+
ms.collection:
12+
- wwl-ai-copilot
13+
ms.custom: devx-track-python
14+
durationInMinutes: 8
15+
content: |
16+
[!include[](includes/2-preprocess-data-configure-featurization.md)]

‎learn-pr/wwl-azure/experiment-azure-machine-learning/3-run-job.yml‎

Lines changed: 16 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,16 @@
1+
### YamlMime:ModuleUnit
2+
uid: learn.wwl.experiment-azure-machine-learning.run-job
3+
title: Run an Automated Machine Learning experiment
4+
metadata:
5+
title: Run an Automated Machine Learning experiment
6+
description: Learn how to configure and submit an automated machine learning experiment run with the Python SDK (v2) for Azure Machine Learning.
7+
author: wwlpublish
8+
ms.author: madiepev
9+
ms.date: 03/11/2026
10+
ms.topic: unit
11+
ms.collection:
12+
- wwl-ai-copilot
13+
ms.custom: devx-track-python
14+
durationInMinutes: 10
15+
content: |
16+
[!include[](includes/3-run-job.md)]

‎learn-pr/wwl-azure/experiment-azure-machine-learning/4-evaluate-compare-models.yml‎

Lines changed: 16 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,16 @@
1+
### YamlMime:ModuleUnit
2+
uid: learn.wwl.experiment-azure-machine-learning.evaluate-compare-models
3+
title: Evaluate and compare models
4+
metadata:
5+
title: Evaluate and compare models
6+
description: Learn how to evaluate and compare models trained by automated machine learning in Azure Machine Learning.
7+
author: wwlpublish
8+
ms.author: madiepev
9+
ms.date: 03/11/2026
10+
ms.topic: unit
11+
ms.collection:
12+
- wwl-ai-copilot
13+
ms.custom: devx-track-python
14+
durationInMinutes: 8
15+
content: |
16+
[!include[](includes/4-evaluate-compare-models.md)]

‎learn-pr/wwl-azure/experiment-azure-machine-learning/5-use-mlflow-model-tracking.yml‎

Lines changed: 16 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,16 @@
1+
### YamlMime:ModuleUnit
2+
uid: learn.wwl.experiment-azure-machine-learning.use-mlflow-model-tracking
3+
title: Configure MLflow for model tracking in notebooks
4+
metadata:
5+
title: Configure MLflow for model tracking in notebooks
6+
description: Learn how to configure MLflow for model tracking when experimenting in notebooks in Azure Machine Learning.
7+
author: wwlpublish
8+
ms.author: madiepev
9+
ms.date: 03/11/2026
10+
ms.topic: unit
11+
ms.collection:
12+
- wwl-ai-copilot
13+
ms.custom: devx-track-python
14+
durationInMinutes: 8
15+
content: |
16+
[!include[](includes/5-use-mlflow-model-tracking.md)]

‎learn-pr/wwl-azure/experiment-azure-machine-learning/6-train-models-notebooks.yml‎

Lines changed: 16 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,16 @@
1+
### YamlMime:ModuleUnit
2+
uid: learn.wwl.experiment-azure-machine-learning.train-models-notebooks
3+
title: Train and track models in notebooks
4+
metadata:
5+
title: Train and track models in notebooks
6+
description: Learn how to train and track models in Jupyter notebooks using MLflow in Azure Machine Learning.
7+
author: wwlpublish
8+
ms.author: madiepev
9+
ms.date: 03/11/2026
10+
ms.topic: unit
11+
ms.collection:
12+
- wwl-ai-copilot
13+
ms.custom: devx-track-python
14+
durationInMinutes: 10
15+
content: |
16+
[!include[](includes/6-train-models-notebooks.md)]

‎learn-pr/wwl-azure/experiment-azure-machine-learning/7-exercise.yml‎

Lines changed: 16 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,16 @@
1+
### YamlMime:ModuleUnit
2+
uid: learn.wwl.experiment-azure-machine-learning.exercise
3+
title: Exercise - Find the best classification model with Azure Machine Learning
4+
metadata:
5+
title: Exercise - Find the best classification model with Azure Machine Learning
6+
description: Practice finding the best classification model by using AutoML and MLflow-tracked notebooks in Azure Machine Learning.
7+
author: wwlpublish
8+
ms.author: madiepev
9+
ms.date: 03/11/2026
10+
ms.topic: unit
11+
ms.collection:
12+
- wwl-ai-copilot
13+
ms.custom: devx-track-python
14+
durationInMinutes: 30
15+
content: |
16+
[!include[](includes/7-exercise.md)]

‎learn-pr/wwl-azure/experiment-azure-machine-learning/8-knowledge-check.yml‎

Lines changed: 60 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,60 @@
1+
### YamlMime:ModuleUnit
2+
uid: learn.wwl.experiment-azure-machine-learning.knowledge-check
3+
title: Module assessment
4+
metadata:
5+
title: Module assessment
6+
description: Test your knowledge on how to use automated machine learning and MLflow in notebooks to find the best classification model in Azure Machine Learning.
7+
author: wwlpublish
8+
ms.author: madiepev
9+
ms.date: 03/11/2026
10+
ms.topic: unit
11+
ms.collection:
12+
- wwl-ai-copilot
13+
module_assessment: true
14+
durationInMinutes: 5
15+
quiz:
16+
questions:
17+
- content: "A data scientist wants to use automated machine learning to find the model with the best AUC_weighted metric. Which parameter of the classification function should be configured?"
18+
choices:
19+
- content: "`task='AUC_weighted'`"
20+
isCorrect: false
21+
explanation: "Incorrect. Task is used to specify whether you're training a classification, regression, or forecasting model."
22+
- content: "`target_column_name='AUC_weighted'`"
23+
isCorrect: false
24+
explanation: "Incorrect. The target is the column you want to predict."
25+
- content: "`primary_metric='AUC_weighted'`"
26+
isCorrect: true
27+
explanation: "Correct. Set the primary metric to the performance score for which you want to optimize the model."
28+
- content: "A data scientist has preprocessed the training data and wants to use automated machine learning to quickly iterate through various algorithms. The data shouldn't be changed. Which featurization mode should they use?"
29+
choices:
30+
- content: "`auto`"
31+
isCorrect: false
32+
explanation: "Incorrect. Auto enables automatic featurization, which transforms the data."
33+
- content: "`custom`"
34+
isCorrect: false
35+
explanation: "Incorrect. Custom enables custom featurization."
36+
- content: "`off`"
37+
isCorrect: true
38+
explanation: "Correct. Setting featurization to off prevents AutoML from applying any preprocessing transformations to the data."
39+
- content: "You want to train a diabetes classification model with the scikit-learn library. You want to focus on experimenting with the model, and minimize the effort needed to log the model's results. Which logging method should you use?"
40+
choices:
41+
- content: "Autologging"
42+
isCorrect: true
43+
explanation: "Correct. You can use autologging with scikit-learn. Enabling autologging minimizes the effort needed to log the model's results."
44+
- content: "Custom logging"
45+
isCorrect: false
46+
explanation: "Incorrect. With custom logging you have to manually log parameters, metrics, and artifacts."
47+
- content: "A combination of autologging and custom logging."
48+
isCorrect: false
49+
explanation: "Incorrect. Custom logging won't minimize the effort."
50+
- content: "When you use MLflow tracking to train a model in a notebook running on Azure Machine Learning compute, on which tab in the studio can you view the model's results?"
51+
choices:
52+
- content: "Data"
53+
isCorrect: false
54+
explanation: "Incorrect. Data shows the registered data assets and datastores."
55+
- content: "Models"
56+
isCorrect: false
57+
explanation: "Incorrect. The Models tab shows registered models."
58+
- content: "Jobs"
59+
isCorrect: true
60+
explanation: "Correct. Jobs shows the MLflow experiment runs including all metadata and logged parameters, metrics, and artifacts."

‎learn-pr/wwl-azure/experiment-azure-machine-learning/9-summary.yml‎

Lines changed: 15 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,15 @@
1+
### YamlMime:ModuleUnit
2+
uid: learn.wwl.experiment-azure-machine-learning.summary
3+
title: Summary
4+
metadata:
5+
title: Summary
6+
description: Summary of how to find the best model with Azure Machine Learning, using AutoML and MLflow-tracked notebooks.
7+
author: wwlpublish
8+
ms.author: madiepev
9+
ms.date: 03/11/2026
10+
ms.topic: unit
11+
ms.collection:
12+
- wwl-ai-copilot
13+
durationInMinutes: 1
14+
content: |
15+
[!include[](includes/9-summary.md)]

‎learn-pr/wwl-azure/experiment-azure-machine-learning/index.yml‎

Lines changed: 44 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,44 @@
1+
### YamlMime:Module
2+
uid: learn.wwl.experiment-azure-machine-learning
3+
metadata:
4+
title: Experiment with Azure Machine Learning
5+
description: Learn how to find the best model with automated machine learning (AutoML) and by experimenting in notebooks.
6+
author: wwlpublish
7+
ms.author: madiepev
8+
ms.date: 03/11/2026
9+
ms.service: azure-machine-learning
10+
ms.topic: module
11+
ms.collection:
12+
- wwl-ai-copilot
13+
title: Experiment with Azure Machine Learning
14+
summary: Learn how to find the best model with automated machine learning (AutoML) and by experimenting in notebooks.
15+
abstract: |
16+
In this module, you'll learn how to:
17+
- Prepare your data to use AutoML for classification.
18+
- Configure and run an AutoML experiment.
19+
- Evaluate and compare AutoML models.
20+
- Configure MLflow for model tracking in notebooks.
21+
- Use MLflow for model tracking in notebooks.
22+
prerequisites: |
23+
None
24+
iconUrl: /training/achievements/find-best-classification-model-automated-machine-learning.svg
25+
levels:
26+
- beginner
27+
roles:
28+
- data-scientist
29+
products:
30+
- azure-machine-learning
31+
subjects:
32+
- machine-learning
33+
units:
34+
- learn.wwl.experiment-azure-machine-learning.introduction
35+
- learn.wwl.experiment-azure-machine-learning.preprocess-data-configure-featurization
36+
- learn.wwl.experiment-azure-machine-learning.run-job
37+
- learn.wwl.experiment-azure-machine-learning.evaluate-compare-models
38+
- learn.wwl.experiment-azure-machine-learning.use-mlflow-model-tracking
39+
- learn.wwl.experiment-azure-machine-learning.train-models-notebooks
40+
- learn.wwl.experiment-azure-machine-learning.exercise
41+
- learn.wwl.experiment-azure-machine-learning.knowledge-check
42+
- learn.wwl.experiment-azure-machine-learning.summary
43+
badge:
44+
uid: learn.wwl.experiment-azure-machine-learning.badge

0 commit comments

Comments
 (0)