Skip to content

Commit e3f5e96

Browse files
authored
Merge pull request #220829 from sdgilley/sdg-maintenance
move PBI tutorial to v1 folder
2 parents 9b1e9a5 + f139153 commit e3f5e96

File tree

9 files changed

+8
-3
lines changed

9 files changed

+8
-3
lines changed

articles/machine-learning/.openpublishing.redirection.machine-learning.json

Lines changed: 5 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -1,5 +1,10 @@
11
{
22
"redirections": [
3+
{
4+
"source_path_from_root": "/articles/machine-learning/tutorial-power-bi-custom-model.md",
5+
"redirect_url": "/azure/machine-learning/v1/tutorial-power-bi-custom-model",
6+
"redirect_document_id": true
7+
},
38
{
49
"source_path_from_root": "/articles/machine-learning/how-to-link-synapse-ml-workspaces.md",
510
"redirect_url": "/azure/machine-learning/v1/how-to-link-synapse-ml-workspaces",

articles/machine-learning/v1/toc.yml

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -71,7 +71,7 @@
7171
- name: Microsoft Power BI integration
7272
items:
7373
- name: "Part 1: Train and deploy models"
74-
href: ../tutorial-power-bi-custom-model.md
74+
href: tutorial-power-bi-custom-model.md
7575
- name: "Part 2: Consume in Power BI"
7676
href: /power-bi/connect-data/service-aml-integrate?context=azure/machine-learning/context/ml-context
7777
- name: Samples (v1)

articles/machine-learning/tutorial-power-bi-custom-model.md renamed to articles/machine-learning/v1/tutorial-power-bi-custom-model.md

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -15,7 +15,7 @@ ms.custom: sdkv1, event-tier1-build-2022
1515

1616
# Tutorial: Power BI integration - Create the predictive model with a Jupyter Notebook (part 1 of 2)
1717

18-
[!INCLUDE [sdk v1](../../includes/machine-learning-sdk-v1.md)]
18+
[!INCLUDE [sdk v1](../../../includes/machine-learning-sdk-v1.md)]
1919

2020
In part 1 of this tutorial, you train and deploy a predictive machine learning model by using code in a Jupyter Notebook. You also create a scoring script to define the input and output schema of the model for integration into Power BI. In part 2, you use the model to predict outcomes in Microsoft Power BI.
2121

@@ -32,7 +32,7 @@ In this tutorial, you:
3232
## Prerequisites
3333

3434
- An Azure subscription. If you don't already have a subscription, you can use a [free trial](https://azure.microsoft.com/free/).
35-
- An Azure Machine Learning workspace. If you don't already have a workspace, see [Create workspace resources](quickstart-create-resources.md).
35+
- An Azure Machine Learning workspace. If you don't already have a workspace, see [Create workspace resources](../quickstart-create-resources.md).
3636
- Introductory knowledge of the Python language and machine learning workflows.
3737

3838
## Create a notebook and compute

0 commit comments

Comments
 (0)