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Move mlmodel design and add one alias
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sguequierre committed Jan 8, 2025
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2 changes: 1 addition & 1 deletion docs/data-ai/ai/deploy.md
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Expand Up @@ -74,5 +74,5 @@ For other use cases, consider [creating custom functionality with a module](/ope

{{< alert title="Add support for other models" color="tip" >}}
ML models must be designed in particular shapes to work with the `mlmodel` [classification](/operate/reference/services/vision/mlmodel/) or [detection](/operate/reference/services/vision/mlmodel/) model of Viam's [vision service](/operate/reference/services/vision/).
See [ML Model Design](/operate/reference/advanced-modules/mlmodel-design/) to design a modular ML model service with models that work with vision.
See [ML Model Design](/data-ai/reference/mlmodel-design/) to design a modular ML model service with models that work with vision.
{{< /alert >}}
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@@ -1,6 +1,6 @@
---
title: "Design your ML Models for Vision"
linkTitle: "ML Model Design"
linkTitle: "ML model service design"
weight: 60
type: "docs"
tags: ["data management", "ml", "model training", "vision"]
Expand All @@ -12,6 +12,7 @@ date: "2022-01-01"
# SME: Bijan Haney
aliases:
- /registry/advanced/mlmodel-design/
- /operate/reference/advanced-modules/mlmodel-design/
---

The [Machine Learning (ML) model service](/data-ai/ai/deploy/) allow you to deploy machine learning models to your smart machine.
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1 change: 1 addition & 0 deletions docs/operate/get-started/other-hardware/_index.md
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Expand Up @@ -17,6 +17,7 @@ aliases:
- /build/program/extend/modular-resources/key-concepts/
- /modular-resources/key-concepts/
- /modular-resources/
- /how-tos/upload-module/
prev: "/operate/get-started/supported-hardware/"
next: "/operate/get-started/other-hardware/hello-world-module/"
---
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2 changes: 1 addition & 1 deletion docs/operate/reference/advanced-modules/_index.md
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Expand Up @@ -50,4 +50,4 @@ However, if you are unable to use modular resources because you need to host `vi

When working with the [ML model service](/dev/reference/apis/services/ml/), you can deploy an [existing model](/data-ai/ai/deploy/) or [train your own model](/data-ai/ai/train/).

However, if you are writing your own {{< glossary_tooltip term_id="module" text="module" >}} that uses the ML model service together with the [vision service](/dev/reference/apis/services/vision/), you can also [design your own ML model](/operate/reference/advanced-modules/mlmodel-design/) to better match your specific use case.
However, if you are writing your own {{< glossary_tooltip term_id="module" text="module" >}} that uses the ML model service together with the [vision service](/dev/reference/apis/services/vision/), you can also [design your own ML model](/data-ai/reference/mlmodel-design/) to better match your specific use case.

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