Merge pull request #2025 from RonanSynnottArm/mlek

Fix links to MLEK

Author: jasonrandrews

content/learning-paths/embedded-and-microcontrollers/mlek/_index.md

@@ -40,7 +40,7 @@ tools_software_languages:
 further_reading:
     - resource:
         title: ML Evaluation Kit Quick Start Guide
-        link: https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ml-embedded-evaluation-kit/+/HEAD/docs/quick_start.md
+        link: https://gitlab.arm.com/artificial-intelligence/ethos-u/ml-embedded-evaluation-kit/-/blob/main/docs/quick_start.md
         type: documentation
     - resource:
         title: Creating ML applications for embedded devices on Arm Virtual Hardware

content/learning-paths/embedded-and-microcontrollers/mlek/build.md

@@ -7,7 +7,7 @@ weight: 2 # 1 is first, 2 is second, etc.
 # Do not modify these elements
 layout: "learningpathall"
 ---
-The [Arm ML Evaluation Kit (MLEK)](https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ml-embedded-evaluation-kit) provides a number of ready-to-use ML applications. These allow you to investigate the embedded software stack and evaluate performance on the Cortex-M55 and Ethos-U85 processors.
+The [Arm ML Evaluation Kit (MLEK)](https://gitlab.arm.com/artificial-intelligence/ethos-u/ml-embedded-evaluation-kit) provides a number of ready-to-use ML applications. These allow you to investigate the embedded software stack and evaluate performance on the Cortex-M55 and Ethos-U85 processors.
 
 You can use the MLEK source code to build sample applications and run them on the [Corstone reference systems](https://www.arm.com/products/silicon-ip-subsystems/), for example the [Corstone-320](https://developer.arm.com/Processors/Corstone-320) Fixed Virtual Platform (FVP).
 
@@ -53,7 +53,7 @@ You can review the installation guides for further details.
 Clone the ML Evaluation Kit repository, and navigate into the new directory:
 
 ```bash
-git clone "https://review.mlplatform.org/ml/ethos-u/ml-embedded-evaluation-kit"
+git clone "https://git.gitlab.arm.com/artificial-intelligence/ethos-u/ml-embedded-evaluation-kit.git"
 cd ml-embedded-evaluation-kit
 git submodule update --init
 ```

content/learning-paths/embedded-and-microcontrollers/mlek/run.md

@@ -72,7 +72,7 @@ The application executes and identifies words spoken within audio files.
 
 Repeat with any of the other built applications.
 
-Full instructions are provided in the evaluation kit [documentation](https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ml-embedded-evaluation-kit/+/HEAD/docs/quick_start.md).
+Full instructions are provided in the evaluation kit [documentation](https://gitlab.arm.com/artificial-intelligence/ethos-u/ml-embedded-evaluation-kit/-/blob/main/docs/quick_start.md).
 
 
 ## Addendum: Speed up FVP execution

content/learning-paths/embedded-and-microcontrollers/nav-mlek/sw.md

@@ -11,7 +11,7 @@ layout: "learningpathall"
 
 You should use an `x86_64` development machine running Windows or Linux for the best experience. 
 
-The [Arm ML Evaluation Kit (MLEK)](https://git.mlplatform.org/ml/ethos-u/ml-embedded-evaluation-kit.git/) is not fully supported on Windows. Some of the required tools work only on Linux. Linux is recommended if you plan to use MLEK extensively. 
+The [Arm ML Evaluation Kit (MLEK)](https://gitlab.arm.com/artificial-intelligence/ethos-u/ml-embedded-evaluation-kit) is not fully supported on Windows. Some of the required tools work only on Linux. Linux is recommended if you plan to use MLEK extensively. 
 
 There are some ML examples which can be developed using Windows tools. 
 
@@ -52,7 +52,7 @@ You may want to use [Docker](/install-guides/docker) to simplify ML development
 As an example, clone the MLEK repository and look at the `Dockerfile` at the top of the repository to see one way to use Docker in ML application development:
 
 ```console
-git clone "https://review.mlplatform.org/ml/ethos-u/ml-embedded-evaluation-kit"
+git clone "https://git.gitlab.arm.com/artificial-intelligence/ethos-u/ml-embedded-evaluation-kit.git"
 cd ml-embedded-evaluation-kit
 git submodule update --init
 ```
@@ -96,9 +96,9 @@ Resources for learning about ML applications are listed below for you to investi
 
 ### Arm ML Evaluation Kit (MLEK)
 
-The [MLEK](https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ml-embedded-evaluation-kit) provides a number of example ML applications.
+The [MLEK](https://gitlab.arm.com/artificial-intelligence/ethos-u/ml-embedded-evaluation-kit) provides a number of example ML applications.
 
-[The Quick Start Guide](https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ml-embedded-evaluation-kit/+/HEAD/docs/quick_start.md) guides you through running an example application.
+[The Quick Start Guide](https://gitlab.arm.com/artificial-intelligence/ethos-u/ml-embedded-evaluation-kit/-/blob/main/docs/quick_start.md) guides you through running an example application.
 
 ### Micro speech
 

content/learning-paths/iot/iot-sdk/openiot.md

@@ -7,7 +7,7 @@ weight: 2 # 1 is first, 2 is second, etc.
 # Do not modify these elements
 layout: "learningpathall"
 ---
-[Arm Total Solutions for IoT](https://www.arm.com/markets/iot/total-solutions-iot) provide reference software stacks, integrating various Arm technologies, such as [Arm Trusted Firmware-M](https://developer.arm.com/Tools%20and%20Software/Trusted%20Firmware-M) and the [Arm ML Evaluation Kit (MLEK)](https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ml-embedded-evaluation-kit).
+[Arm Total Solutions for IoT](https://www.arm.com/markets/iot/total-solutions-iot) provide reference software stacks, integrating various Arm technologies, such as [Arm Trusted Firmware-M](https://developer.arm.com/Tools%20and%20Software/Trusted%20Firmware-M) and the [Arm ML Evaluation Kit (MLEK)](https://gitlab.arm.com/artificial-intelligence/ethos-u/ml-embedded-evaluation-kit).
 
 The [Open-IoT-SDK](https://github.com/ARM-software/open-iot-sdk) is designed to be used with [Arm Virtual Hardware (AVH)](https://www.arm.com/products/development-tools/simulation/virtual-hardware), which provides [Corstone-300](https://developer.arm.com/Processors/Corstone-300) Virtual Hardware.