Merge pull request #1266 from jasonrandrews/spelling

Spelling and link fixes

.wordlist.txt

@@ -3173,4 +3173,18 @@ tps
 uQ
 vulkan
 vulkanised
-writeTemperaturesUrl
+writeTemperaturesUrl
+IPython
+NeuralNetwork
+Sigmoid
+Softmax
+Tanh
+backpropagation
+diskio
+feedforward
+logits
+prem
+softmax
+subclassing
+tanh
+torchsummary

content/learning-paths/cross-platform/eigen-linear-algebra-on-arm/_next-steps.md

@@ -8,10 +8,6 @@ further_reading:
         title: Eigen official Tutorial on Matrix class
         link: https://libeigen.gitlab.io/docs/group__TutorialMatrixClass.html
         type: documentation
-    - resource:
-        title: CS Tutorial on Eigen
-        link: https://cs2240.graphics/assignments/eigen_tutorial.pdf
-        type: documentation
     - resource:
         title: Eigen Webinar from Linaro
         link: https://static.linaro.org/connect/webinars/presentations/Eigen_Webinar_3.pdf

content/learning-paths/embedded-systems/_index.md

@@ -52,7 +52,6 @@ tools_software_languages_filter:
 - Kubernetes: 1
 - LLM: 2
 - Matter: 1
-- ML: 1
 - MXNet: 1
 - Neon: 1
 - Porcupine: 1

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

@@ -11,9 +11,9 @@ operatingsystems_filter:
 - Android: 2
 - Baremetal: 1
 - ChromeOS: 1
-- Linux: 23
-- macOS: 3
-- Windows: 31
+- Linux: 24
+- macOS: 4
+- Windows: 32
 subjects_filter:
 - CI-CD: 3
 - Containers and Virtualization: 5
@@ -24,6 +24,7 @@ title: Laptops and Desktops
 tools_software_languages_filter:
 - .NET: 12
 - Alacritty: 1
+- Android Studio: 1
 - Arm Development Studio: 2
 - Arm64EC: 1
 - C: 2
@@ -32,7 +33,7 @@ tools_software_languages_filter:
 - C/C++: 4
 - Clang: 8
 - CMake: 2
-- Coding: 15
+- Coding: 16
 - CSS: 1
 - Docker: 4
 - GCC: 8

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

@@ -10,7 +10,7 @@ layout: "learningpathall"
 In this section, you connect the emulator to AWS IoT Core.
 
 ## Connecting the emulator
-Log in to the AWS Console at https://www.console.aws.amazon.com, and then search for IoT. From the list that appears, select **IoT Core**:
+Log in to the AWS Console at https://aws.amazon.com, and then search for IoT. From the list that appears, select **IoT Core**:
 
 ![fig1](Figures/01.png)
 

content/learning-paths/servers-and-cloud-computing/_index.md

@@ -9,29 +9,30 @@ maintopic: true
 operatingsystems_filter:
 - Android: 2
 - Baremetal: 1
-- Linux: 95
-- macOS: 4
-- Windows: 7
+- Linux: 100
+- macOS: 6
+- Windows: 9
 pinned_modules:
 - module:
     name: Recommended getting started learning paths
     paths:
     - providers
     - migration
 subjects_filter:
-- CI-CD: 2
-- Containers and Virtualization: 23
+- CI-CD: 3
+- Containers and Virtualization: 24
 - Databases: 15
 - Libraries: 6
-- ML: 8
+- ML: 10
 - Performance and Architecture: 35
 - Storage: 1
-- Web: 9
+- Web: 10
 subtitle: Optimize cloud native apps on Arm for performance and cost
 title: Servers and Cloud Computing
 tools_software_languages_filter:
 - .NET SDK: 1
 - 5G: 1
+- Android Studio: 1
 - Ansible: 2
 - Arm Development Studio: 4
 - armclang: 1
@@ -40,6 +41,7 @@ tools_software_languages_filter:
 - ASP.NET Core: 2
 - Assembly: 4
 - AWS CodeBuild: 1
+- AWS EC2: 1
 - AWS Elastic Container Service (ECS): 1
 - AWS Elastic Kubernetes Service (EKS): 2
 - Bastion: 3
@@ -55,8 +57,9 @@ tools_software_languages_filter:
 - Clang: 9
 - ClickBench: 1
 - ClickHouse: 1
+- CloudFormation: 1
 - CMake: 1
-- Coding: 16
+- Coding: 17
 - Django: 1
 - Docker: 14
 - Envoy: 2
@@ -66,8 +69,8 @@ tools_software_languages_filter:
 - GCC: 17
 - gdb: 1
 - Geekbench: 1
-- GenAI: 2
-- GitHub: 1
+- GenAI: 3
+- GitHub: 2
 - GitLab: 1
 - Glibc: 1
 - Go: 2
@@ -81,11 +84,11 @@ tools_software_languages_filter:
 - JAX: 1
 - Kafka: 1
 - Keras: 1
-- Kubernetes: 7
+- Kubernetes: 8
 - Lambda: 1
 - libbpf: 1
 - Linaro Forge: 1
-- LLM: 1
+- LLM: 2
 - LSE: 1
 - MariaDB: 1
 - Memcached: 2
@@ -96,12 +99,12 @@ tools_software_languages_filter:
 - NEON: 1
 - Nexmark: 1
 - Nginx: 3
-- Node.js: 2
+- Node.js: 3
 - PAPI: 1
 - perf: 3
 - PostgreSQL: 4
-- Python: 8
-- PyTorch: 3
+- Python: 9
+- PyTorch: 4
 - Redis: 3
 - Remote.It: 2
 - RME: 2
@@ -121,14 +124,14 @@ tools_software_languages_filter:
 - Trusted Firmware: 1
 - TypeScript: 1
 - Vectorscan: 1
-- Visual Studio Code: 2
+- Visual Studio Code: 3
 - WordPress: 3
 - x265: 1
 - zlib: 1
 - Zookeeper: 1
 weight: 1
 cloud_service_providers_filter:
-- AWS: 11
+- AWS: 13
 - Google Cloud: 8
 - Microsoft Azure: 7
 - Oracle: 2

content/learning-paths/servers-and-cloud-computing/intro/find-hardware.md

@@ -18,7 +18,7 @@ Cloud providers offer Arm instances based on Neoverse processors. For example:
 - [Microsoft Azure](https://azure.microsoft.com/en-us/blog/azure-virtual-machines-with-ampere-altra-arm-based-processors-generally-available/)
 - [Oracle Cloud](https://www.oracle.com/cloud/compute/arm/)
 - [Equinix](https://deploy.equinix.com/product/servers/c3-large-arm64/)
-- [Scaleway](https://www.scaleway.com/en/amp2-instances/)
+- [Scaleway](https://www.scaleway.com/en/cost-optimized-instances-based-on-arm/)
 - [Hetzner Cloud](https://www.hetzner.com/news/arm64-cloud)
 
 Free tier offers are currently available.

content/learning-paths/servers-and-cloud-computing/mongodb/benchmark_mongodb.md

@@ -9,7 +9,7 @@ layout: "learningpathall"
 ---
 To further measure the performance of MongoDB, you will run the [Yahoo Cloud Serving Benchmark](http://github.com/brianfrankcooper/YCSB).
 
-[YCSB](https://research.yahoo.com/news/yahoo-cloud-serving-benchmark/) is an open sourced project which provides the framework and common set of workloads to evaluate the performance of different "key-value" and "cloud" serving stores. Here are the steps to run YCSB to evaluate the performance of MongoDB running on 64-bit Arm machine.
+YCSB is an open sourced project which provides the framework and common set of workloads to evaluate the performance of different "key-value" and "cloud" serving stores. Here are the steps to run YCSB to evaluate the performance of MongoDB running on 64-bit Arm machine.
 
 ## Additional software packages
 

content/learning-paths/servers-and-cloud-computing/serverless-framework-aws-s3/_index.md

@@ -19,7 +19,7 @@ author_primary: Dawid Borycki
 ### Tags
 skilllevels: Introductory
 subjects: Web
-cloud_service_providers: Amazon Web Services
+cloud_service_providers: AWS
 
 armips:
     - Neoverse
@@ -31,7 +31,7 @@ tools_software_languages:
 operatingsystems:
     - Linux
     - Windows
-    - MacOS
+    - macOS
 
 
 ### FIXED, DO NOT MODIFY

content/learning-paths/smartphones-and-mobile/_index.md

@@ -10,14 +10,14 @@ key_ip:
 - Mali
 maintopic: true
 operatingsystems_filter:
-- Android: 20
-- Linux: 15
-- macOS: 5
-- Windows: 4
+- Android: 21
+- Linux: 16
+- macOS: 6
+- Windows: 5
 subjects_filter:
 - Gaming: 6
-- Graphics: 2
-- ML: 4
+- Graphics: 3
+- ML: 5
 - Performance and Architecture: 22
 subtitle: Optimize Android apps and build faster games using cutting-edge Arm tech
 title: Smartphones and Mobile
@@ -27,7 +27,7 @@ tools_software_languages_filter:
 - Android: 2
 - Android NDK: 1
 - Android SDK: 1
-- Android Studio: 5
+- Android Studio: 6
 - Arm Development Studio: 1
 - Arm Mobile Studio: 1
 - Arm Performance Studio: 2
@@ -37,7 +37,7 @@ tools_software_languages_filter:
 - C/C++: 1
 - Clang: 8
 - CMake: 1
-- Coding: 13
+- Coding: 15
 - Fixed Virtual Platform: 1
 - Frame Advisor: 1
 - GCC: 9
@@ -60,7 +60,7 @@ tools_software_languages_filter:
 - Trusted Firmware: 1
 - Unity: 6
 - Unreal Engine: 2
-- Vulkan: 1
+- Vulkan: 2
 - XNNPACK: 1
 weight: 3
 ---