Edits based on new suggestions

1) Changed MV2 intro to "uses the MobileNet v2 model to classify images." since current runner doesn't have camera integration
2) reworded conda env setup
3) added escape character for backslashes
4) mentioned MV2 model output values represent class scores

Author: nil-is-all

docs/source/using-executorch-windows.md

@@ -3,9 +3,7 @@
 This document outlines the current known working build instructions for building and validating ExecuTorch on a Windows machine.
 
 This demo uses the
-[MobileNet v2](https://pytorch.org/vision/main/models/mobilenetv2.html) model to
-process live camera images leveraging the
-[XNNPACK](https://github.com/google/XNNPACK) backend.
+[MobileNet v2](https://pytorch.org/vision/main/models/mobilenetv2.html) model to classify images using the [XNNPACK](https://github.com/google/XNNPACK) backend.
 
 Note that all commands should be executed on Windows powershell in administrator mode.
 
@@ -25,7 +23,8 @@ Install ClangCL for Windows from the [official website](https://learn.microsoft.
 To check if conda is detected by the powershell prompt, try `conda list` or `conda --version`
 
 If conda is not detected, you could run the powershell script for conda named `conda-hook.ps1`.
-
+To verify that Conda is available in the in the powershell environment, run try `conda list` or `conda --version`. 
+If Conda is not available, run conda-hook.ps1 as follows:
 ```bash
 $miniconda_dir\\shell\\condabin\\conda-hook.ps1
 ```
@@ -116,8 +115,8 @@ python .\\export_mv2.py
 del -Recurse -Force cmake-out; `
 cmake . `
   -DCMAKE_INSTALL_PREFIX=cmake-out `
-  -DPYTHON_EXECUTABLE=C:\Users\nikhi\miniconda3\envs\et\python.exe `
-  -DCMAKE_PREFIX_PATH=C:\Users\nikhi\miniconda3\envs\et\Lib\site-packages `
+  -DPYTHON_EXECUTABLE=$miniconda_dir\\envs\\et\\python.exe `
+  -DCMAKE_PREFIX_PATH=$miniconda_dir\\envs\\et\\Lib\\site-packages `
   -DCMAKE_BUILD_TYPE=Release `
   -DEXECUTORCH_BUILD_EXTENSION_TENSOR=ON `
   -DEXECUTORCH_BUILD_FLATC=ON `
@@ -131,14 +130,16 @@ cmake . `
   -Bcmake-out; `
 cmake --build cmake-out -j64 --target install --config Release
 ```
+where `$miniconda_dir` is the directory where you installed miniconda
+This is `“C:\Users\<username>\AppData\Local”` by default.
 
 ## Run Mobilenet V2 model with XNNPACK delegation
 
 ```bash
-.\cmake-out\backends\xnnpack\Release\xnn_executor_runner.exe --model_path=.\mv2_xnnpack.pte
+.\\cmake-out\\backends\\xnnpack\\Release\\xnn_executor_runner.exe --model_path=.\\mv2_xnnpack.pte
 ```
 
-The expected output would print a tensor of size 1x1000.
+The expected output would print a tensor of size 1x1000, containing values of class scores.
 
 ```bash
 Output 0: tensor(sizes=[1, 1000], [