NXP backend: Add NXP backend tutorial page (#14853)

### Summary
Adds tutorial page for NXP backend.

### Test plan
Documentation built locally using Makefile without any problems.

cc @robert-kalmar @JakeStevens @digantdesai

Co-authored-by: Šimon Strýček <[email protected]>

Author: pytorchbot

docs/source/backends-nxp.md

@@ -1,5 +1,40 @@
 # NXP eIQ Neutron Backend
 
-See
-[NXP eIQ Neutron Backend](https://github.com/pytorch/executorch/blob/main/backends/nxp/README.md)
-for current status about running ExecuTorch on NXP eIQ Neutron Backend.
+This manual page is dedicated to introduction of using the ExecuTorch with NXP eIQ Neutron Backend.
+NXP offers accelerated machine learning models inference on edge devices.
+To learn more about NXP's machine learning acceleration platform, please refer to [the official NXP website](https://www.nxp.com/applications/technologies/ai-and-machine-learning:MACHINE-LEARNING).
+
+<div class="admonition tip">
+For up-to-date status about running ExecuTorch on Neutron Backend please visit the <a href="https://github.com/pytorch/executorch/blob/main/backends/nxp/README.md">manual page</a>.
+</div>
+
+## Features
+
+Executorch v1.0 supports running machine learning models on selected NXP chips (for now only i.MXRT700).
+Among currently supported machine learning models are:
+- Convolution-based neutral networks
+- Full support for MobileNetv2 and CifarNet
+
+## Prerequisites (Hardware and Software)
+
+In order to succesfully build executorch project and convert models for NXP eIQ Neutron Backend you will need a computer running Windows or Linux.
+
+If you want to test the runtime, you'll also need:
+- Hardware with NXP's [i.MXRT700](https://www.nxp.com/products/i.MX-RT700) chip or a testing board like MIMXRT700-AVK
+- [MCUXpresso IDE](https://www.nxp.com/design/design-center/software/development-software/mcuxpresso-software-and-tools-/mcuxpresso-integrated-development-environment-ide:MCUXpresso-IDE) or [MCUXpresso Visual Studio Code extension](https://www.nxp.com/design/design-center/software/development-software/mcuxpresso-software-and-tools-/mcuxpresso-for-visual-studio-code:MCUXPRESSO-VSC)
+
+## Using NXP backend 
+
+To test converting a neural network model for inference on NXP eIQ Neutron Backend, you can use our example script:
+
+```shell
+# cd to the root of executorch repository
+./examples/nxp/aot_neutron_compile.sh [model (cifar10 or mobilenetv2)]
+```
+
+For a quick overview how to convert a custom PyTorch model, take a look at our [exmple python script](https://github.com/pytorch/executorch/tree/release/1.0/examples/nxp/aot_neutron_compile.py).
+
+## Runtime Integration
+
+To learn how to run the converted model on the NXP hardware, use one of our example projects on using executorch runtime from MCUXpresso IDE example projects list.
+For more finegrained tutorial, visit [this manual page](https://mcuxpresso.nxp.com/mcuxsdk/latest/html/middleware/eiq/executorch/docs/nxp/topics/example_applications.html).