# Tag: MacOS

## Learning paths

- [Quantize neural upscaling models with ExecuTorch](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/quantize-neural-upscaling-models/)
- [Prepare models for neural graphics with Arm neural technology](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/preparing-models-for-nt/)
- [Profile Android game performance in Godot with Arm Performance Studio](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/godot_packages/)
- [Deploy optimized ML models with ONNX Runtime on Arm platforms](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/onnx/)
- [Accelerate matrix multiplication performance with SME2](https://learn.arm.com/learning-paths/cross-platform/multiplying-matrices-with-sme2/)
- [Install tools on the command line using vcpkg](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/vcpkg-tool-installation/)
- [Convert uvprojx-based projects to csolution](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/uvprojx-conversion/)
- [Visualize Ethos-U NPU performance with ExecuTorch on Arm FVPs](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/visualizing-ethos-u-performance/)
- [Run a computer vision model on a Himax microcontroller](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/yolo-on-himax/)
- [Deploy multi-network device meshes using Device Connect server and NATS](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/device-connect-server/)
- [Use Linux on the NXP FRDM i.MX 93 board](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/linux-nxp-board/)
- [Implement post-quantum cryptography on Arm Cortex-M4](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/pqc_pqm4/)
- [Deploy ExecuTorch firmware on NXP FRDM i.MX 93 for Ethos-U65 acceleration](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/observing-ethos-u-on-nxp/)
- [Run MNIST on an Alif E8 Ensemble DevKit using ExecuTorch and Ethos-U85](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/observing-ethos-u-on-alif/)
- [Accelerate Denoising, Background Blur and Low-Light Camera Effects with SME2](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/ai-camera-pipelines/)
- [Detect faces with OpenCV on Android Devices](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/android_opencv_facedetection/)
- [Build a customer support chatbot on Android with Llama and ExecuTorch](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/customer-support-chatbot-with-llama-and-executorch-on-arm-based-mobile-devices/)
- [Build and profile a simple WebGPU Android Application](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/android_webgpu_dawn/)
- [Build an Android chat app with Llama, KleidiAI, ExecuTorch, and XNNPACK](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/build-llama3-chat-android-app-using-executorch-and-xnnpack/)
- [Learn SVE and SME programming with SIMD Loops](https://learn.arm.com/learning-paths/cross-platform/simd-loops/)
- [Deploy containerized workloads to Arm-based Linux targets with Topo](https://learn.arm.com/learning-paths/cross-platform/deploy-containerized-workloads-with-topo/)
- [Develop a native C++ library on an Arm-based machine](https://learn.arm.com/learning-paths/cross-platform/matrix/)
- [Use LLVM Machine Code Analyzer to analyze assembly performance on Arm](https://learn.arm.com/learning-paths/cross-platform/mca-godbolt/)
- [Profile ExecuTorch models with SME2 on Arm](https://learn.arm.com/learning-paths/cross-platform/sme-executorch-profiling/)
- [Create and train a PyTorch model for digit classification using the MNIST dataset](https://learn.arm.com/learning-paths/cross-platform/pytorch-digit-classification-arch-training/)
- [Access remote devices with Remote.It](https://learn.arm.com/learning-paths/cross-platform/remoteit/)
- [Run and benchmark BitNet-2B inference on Arm CPUs with Litespark-Inference](https://learn.arm.com/learning-paths/cross-platform/litespark-inference/)
- [Optimize exponential functions with FEXPA](https://learn.arm.com/learning-paths/servers-and-cloud-computing/fexpa/)
- [Deploy and integrate AWS Lambda with DynamoDB using the Serverless Framework](https://learn.arm.com/learning-paths/servers-and-cloud-computing/serverless-framework-aws-lambda-dynamodb/)
- [Deploy a static website to Amazon S3 and integrate with AWS Lambda and DynamoDB using the Serverless Framework](https://learn.arm.com/learning-paths/servers-and-cloud-computing/serverless-framework-aws-s3/)
- [Add Arm nodes to your GKE cluster using a multi-architecture Ollama container image](https://learn.arm.com/learning-paths/servers-and-cloud-computing/multiarch_ollama_on_gke/)
- [Automate x86 to Arm Migration with Docker MCP Toolkit, VS Code and GitHub Copilot](https://learn.arm.com/learning-paths/servers-and-cloud-computing/docker-mcp-toolkit/)
- [Run AI models with Docker Model Runner](https://learn.arm.com/learning-paths/laptops-and-desktops/docker-models/)
- [Build and test KleidiCV on macOS](https://learn.arm.com/learning-paths/laptops-and-desktops/kleidicv-on-mac/)
- [Get started with the arm-performix agent skill for profiling and improving Arm workloads](https://learn.arm.com/learning-paths/servers-and-cloud-computing/performix-llm-agent-skill/)
- [Inspect model artifacts and runtime profiles with Google Model Explorer and Arm extensions](https://learn.arm.com/learning-paths/cross-platform/explore-model-artifacts-with-model-explorer/)
- [Deploy a machine learning application to the Arm Ethos-U65 NPU on NXP FRDM i.MX 93 with Topo](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/deploy-ml-model-to-npu-with-topo/)
- [Create and deploy a custom Topo Project](https://learn.arm.com/learning-paths/cross-platform/create-your-own-topo-project/)
- [Run a local AI agent with Ollama to visualize CPU orchestration on Arm](https://learn.arm.com/learning-paths/cross-platform/ai-agent-cpu-orchestration/)
- [Device-to-Device communication with Device Connect](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/device-connect-d2d/)
- [Getting started with CMSIS-DSP using Python](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/cmsisdsp-dev-with-python/)
- [Build IoT Solutions in Azure for Arm Devices](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/azure-iot/)
- [Accelerate multimodal Voice Assistant performance with KleidiAI and SME2](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/voice-assistant/)
- [Learn about function multiversioning](https://learn.arm.com/learning-paths/cross-platform/function-multiversioning/)
- [Build an edge AI Reachy Mini app with Raspberry Pi, MediaPipe, and MuJoCo](https://learn.arm.com/learning-paths/cross-platform/build-a-reachy-robot-app-on-pi/)
- [Run an end-to-end attestation flow with Arm CCA and Trustee](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cca-trustee/)
- [Run Confidential Containers with encrypted images using Arm CCA and Trustee](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cca-kata/)
- [Explore secure device attach in Arm CCA Realms](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cca-device-attach/)
- [Automate MCP server testing using Pytest and Testcontainers](https://learn.arm.com/learning-paths/cross-platform/automate-mcp-with-testcontainers/)
- [Optimize graphics performance using Frame Advisor render graphs](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/render-graph-optimization/)
- [Install and Use Arm integration packages for Unity](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/unity_packages/)
- [Generate audio with Stable Audio Open Small using ExecuTorch](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/run-stable-audio-with-executorch/)
- [Build a Sentiment-Aware Voice Assistant with On-Device LLMs](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/voice-sentiment-analysis-with-llm/)