Merge pull request #708 from jasonrandrews/spelling

spelling updates

Author: jasonrandrews

.wordlist.txt

@@ -2032,4 +2032,178 @@ uv
 uvmpw
 libhugtlbfs
 mcpu
-NoLSE
+NoLSE
+AEMvA
+ActAgent
+AgentDrArmComponent
+AgentsSettings
+AppManager
+ApplyMlMovement
+AttributeError
+BaseViewModel
+BehaviorParametersComponent
+BehaviourName
+BehaviourParameters
+BindingContext
+CEF
+CEF's
+CanExecute
+CanExecuteChanged
+Cinemachine
+CollateObservations
+Compiling Dictionary...
+ComputationTime
+ContentPage
+DComponent
+DOM
+DataPoint
+DataPoints
+DecisionRequester
+DecisionRequesterComponent
+DesktopApp
+DirectX
+DontDestroyOnLoad
+ESM
+EZ
+FMADD
+FontSize
+FontWeight
+GEMV
+GenerateRandomMatrix
+ICommand
+INotifyPropertyChanged
+ISB
+JSONPlaceholder
+LINQ
+ListBox
+LongPath
+MLAgents
+MLPlayerManagerComponent
+MLPs
+MVVM
+MainPage
+MainViewModel
+MainWindow
+MatrixHelper
+MatrixMultiplication
+MaxStep
+MeasurePerformance
+Misspelled words:
+MlPlayerManager
+MobileApp
+MonoBehaviour
+Multilayer
+NextDouble
+NuGet
+NumberBox
+NumberBoxExecutionCount
+NumberBoxMatrixSize
+NumericUpDown
+OnActionReceived
+OnLaunched
+OnPropertyChanged
+PFR
+Perceptrons
+PlayerInput
+PlotResultsCommand
+PropertyChanged
+RESTful
+RayPerceptionSensor
+ReadyToPlay
+Realtime
+RunCalculationsCommand
+Running Task: Markdown...
+SME
+SMSTART
+SVCR
+SVL
+SerializeField
+SetProperty
+SettingsController
+SfChart
+SimpleCommand
+Syncfusion
+TFP
+TODO
+TableLayoutPanel
+TargetType
+TensorBoard
+TextBlock
+Theobald
+ThirdPersonCameraMovement
+Timestep
+Typicode
+UWP
+UnityEngine
+Using aspell to spellcheck Markdown
+VfxService
+ViewModel
+ViewModels
+Walkthrough
+WinForms
+WinUI
+WinUIApp
+WindowsForms
+XAML
+XY
+XamarinForms
+Xn
+ZA
+ZT
+appOutDir
+archs
+async
+axios
+bitfield
+blockMapFile
+blockmap
+bool
+buttonStart
+ce
+cef
+chromiumembedded
+codebase
+coe
+computationTime
+computationTimeHistory
+distributables
+doumentation
+electronjs
+executionCount
+firstrun
+gameplay
+halfwords
+incentivize
+isPlayer
+jQuery
+jsonplaceholder
+labelArchitecture
+listBox
+listBoxResults
+mana
+matLeft
+matResult
+matRight
+matmul
+microservice
+mvvm
+netdesktop
+nsis
+numericUpDownExecutionCount
+numericUpDownMatrixSize
+oneClick
+onwards
+perMachine
+pypi
+raycast
+realtime
+resizable
+scrollable
+sindresorhus
+timeScale
+toolkit's
+windowsarm
+winforms
+winui
+xamarin
+xaml

content/learning-paths/cross-platform/sme/matrix-multiply-example.md

@@ -56,7 +56,7 @@ Execution can be controlled by the `Debug Control` pane icon bar (eg `Step Instr
 1. In the Registers view, expand AArch64 > System > ID > ID_AA64PFR1_EL1. Notice the SME bits are set to 2, meaning the SME2 architectural state and programmers model are implemented on this target.
 2. This bit can also be inspected in the Commands view, by entering `output $AArch64::$System::$ID::$ID_AA64PFR1_EL1.SME`. Other bits in other registers may be inspected similarly.
 3. In the Registers view, expand AArch64 > System > PSTATE > SVCR. Notice the ZA bit is currently 0, meaning the ZA array storage is invalid and not accessible. This will change to 1 later, when an SMSTART instruction is executed.
-4. In `main.c`, observe that `main()` initialises the sizes (M, N, K) of the matrices, prints a welcome banner, then disables SVE and SIMD traps.
+4. In `main.c`, observe that `main()` initializes the sizes (M, N, K) of the matrices, prints a welcome banner, then disables SVE and SIMD traps.
 5. Set a breakpoint on the `disable_sve_traps` function with `break disable_sve_traps` and run to it (press F8). It is written in assembler.
 6. In the Registers view, expand AArch64 > System > Secure > CPTR_EL3. To avoid SME, SVE, or SIMD instructions being trapped, the ESM and EZ bits must be set to 1 and the TFP bit must be cleared to 0, respectively, in CPTR_EL3. These bits reset to an architecturally unknown value on startup.
 7. In the Debug Control view, select Stepping By Instruction (press F10) to switch stepping mode to instruction level.

content/learning-paths/laptops-and-desktops/electron/how-to-1.md

@@ -308,4 +308,4 @@ You now have the application up and running. By default, it runs using the Arm64
 
 ![fig4](Figures/04.png)
 
-In the next step, you will configure your application such that you can explcitly build it for x64 and Arm64 platforms.
+In the next step, you will configure your application such that you can explicitly build it for x64 and Arm64 platforms.

content/learning-paths/laptops-and-desktops/win_cef/how-to-1.md

@@ -299,4 +299,4 @@ After re-running the application you will see the following:
 ![fig4](Figures/04.png)
 
 ## Summary
-CEF is a powerful tool for integrating web browser functionalities into desktop applications, utilizing modern web technologies. You have learnt how to setup a project, create a basic application, and using CMake for CEF projects. Additionally, you explored more advanced features like fetching and displaying data from JSONPlaceholder, adding and styling HTML elements like tables and buttons through separate CSS files all on your Windows on Arm machine.
+CEF is a powerful tool for integrating web browser functionalities into desktop applications, utilizing modern web technologies. You have learned how to setup a project, create a basic application, and using CMake for CEF projects. Additionally, you explored more advanced features like fetching and displaying data from JSONPlaceholder, adding and styling HTML elements like tables and buttons through separate CSS files all on your Windows on Arm machine.

content/learning-paths/laptops-and-desktops/win_forms/how-to-2.md

@@ -39,7 +39,7 @@ Next, launch the application for the Arm64 platform. Run the matrix multiplicati
 By comparing the execution times, we observe that, on average, Arm64 provides almost a 30% performance improvement over x64.
 
 ## Summary
-In this learning path, you learnt how to develop and optimize a desktop application using Windows Forms in .NET on Arm64, particularly for matrix multiplication operations. 
+In this learning path, you learned how to develop and optimize a desktop application using Windows Forms in .NET on Arm64, particularly for matrix multiplication operations. 
 
 You started with an overview of Windows Forms, a GUI class library in .NET, and its role in developing desktop applications. Then, you created a new Windows Forms project in Visual Studio, including setting up the project environment and selecting the appropriate .NET Framework version. You created both the user interface for this application and implemented the application logic.
 

content/learning-paths/laptops-and-desktops/win_winui3/_index.md

@@ -11,7 +11,7 @@ learning_objectives:
 
 prerequisites:
     - A Windows on Arm computer such as [Windows Dev Kit 2023](https://learn.microsoft.com/en-us/windows/arm/dev-kit), Lenovo Thinkpad X13s running Windows 11 or a Windows on Arm[virtual machine](/learning-paths/cross-platform/woa_azure/).
-    - "Visual Studio 2022 with two workloads: .NET desktop developmentt, and Universal Windows Platform development."
+    - "Visual Studio 2022 with two workloads: .NET desktop development, and Universal Windows Platform development."
 
 author_primary: Dawid Borycki
 

content/learning-paths/laptops-and-desktops/win_winui3/how-to-2.md

@@ -27,4 +27,4 @@ Next, launch the application for the ARM64 platform. Execute matrix multiplicati
 Upon comparing the execution times, it is observed that ARM64, on average, provides almost a 50% performance improvement over x64.
 
 ## Summary
-In this learning path, you learnt how to develop a WinUI 3 application, run it in different modes (x64 and Arm64) to compare the performance in matrix multiplication tasks. This comparison was essential to understand the efficiency and speed of execution in different architectural settings. 
+In this learning path, you learned how to develop a WinUI 3 application, run it in different modes (x64 and Arm64) to compare the performance in matrix multiplication tasks. This comparison was essential to understand the efficiency and speed of execution in different architectural settings. 

content/learning-paths/servers-and-cloud-computing/aws-copilot/app.md

@@ -7,7 +7,7 @@ layout: "learningpathall"
 
 [AWS Copilot CLI](https://aws.github.io/copilot-cli/) is an open source command line interface for running containers on AWS App Runner, Amazon Elastic Container Service (ECS), and AWS Fargate. 
 
-You can use Copilot to run containers on Fargate’s serverless compute with Graviton2 processors and benefit from improved price performance. 
+You can use Copilot to run containers on Fargate serverless compute with Graviton2 processors and benefit from improved price performance. 
 
 Graviton2 is not the default for Copilot, but read on to find out how to set the architecture to Arm.
 

content/learning-paths/smartphones-and-mobile/using_unity_machine_learning_agents/07-Objects-and-Components.md

@@ -107,7 +107,7 @@ We need to add some code to make the character aware of some health statistics f
     }
     ```
 
-1. In the script, scroll down to the _CollectObservations()_ method. This method collates information that is key to the reinforcment learning process to help the ML Agent make good decisions. Various bits of state information are returned as a list of observations, such as:
+1. In the script, scroll down to the _CollectObservations()_ method. This method collates information that is key to the reinforcement learning process to help the ML Agent make good decisions. Various bits of state information are returned as a list of observations, such as:
 
     * Roll/dodge flag (is the character currently rolling/dodging)
 
@@ -156,7 +156,7 @@ We need to add some code to make the character aware of some health statistics f
 
 ### Edit BattleEnvController.cs
 
-1. Now select the _AgentsSettings_ object, in the _Hierachy_ tab, on the left.
+1. Now select the _AgentsSettings_ object, in the _Hierarchy_ tab, on the left.
 
 ![Agent Settings](images/heirachy-agent-settings.png "Figure 7. Agent Settings")
 

content/learning-paths/smartphones-and-mobile/using_unity_machine_learning_agents/08-Training-our-ML-agents.md

@@ -46,7 +46,7 @@ https://www.python.org/downloads/
 
 ### Installing PyTorch and ML Agents
 
-_Note 1._ If you are using a command prompt or PowerShell you may need to run with administrator permissons.
+_Note 1._ If you are using a command prompt or PowerShell you may need to run with administrator permissions.
 
 _Note 2._ In Windows you may need to enable [LongPath support](https://pip.pypa.io/warnings/enable-long-paths).
 
@@ -178,7 +178,7 @@ Once the training scene is loaded, it should look similar to this:
 
 The training takes a long time, so we recommend using a CUDA GPU to be faster. However, it is possible to run the training on the CPU.
 
-_Note._ If you do not have an NVidia GPU that supports CUDA, you may see the following warning.
+_Note._ If you do not have an NVIDIA GPU that supports CUDA, you may see the following warning.
 
 ```
 UserWarning: CUDA initialization: Found no NVIDIA driver on your system.
@@ -526,7 +526,7 @@ We have already prepared 3 data files; one for each difficulty level. If you hav
 
     `Assets->#DevSummit2022->Scenes->Level_DevSummit2022`
 
-1. Now select the _AgentsSettings_ object, in the _Hierachy_ tab (normally on the left).
+1. Now select the _AgentsSettings_ object, in the _Hierarchy_ tab (normally on the left).
 
     ![Agent Settings](images/heirachy-agent-settings.png "Figure 1. Agents Settings")