Skill UI

A comprehensive, multi-phased workflow bundle designed for building production-grade AI and Machine Learning applications. It guides users through key stages, including AI application design, RAG implementation, autonomous agent development, robust ML pipelines, AI observability setup, and security hardening.

A comprehensive, multi-phased workflow bundle designed for building production-grade AI and Machine Learning applications. It guides users through key stages, including AI application design, RAG implementation, autonomous agent development, robust ML pipelines, AI observability setup, and security hardening.

This comprehensive Python SDK serves as a client library for managing the full lifecycle of Machine Learning resources on Azure Machine Learning. It allows users to programmatically handle workspaces, register data and models, provision compute clusters, define complex training jobs, and build reproducible, end-to-end MLOps pipelines.

This comprehensive Python SDK serves as a client library for managing the full lifecycle of Machine Learning resources on Azure Machine Learning. It allows users to programmatically handle workspaces, register data and models, provision compute clusters, define complex training jobs, and build reproducible, end-to-end MLOps pipelines.

A comprehensive SDK providing robust authentication credentials for Python applications interacting with Azure services. It simplifies secure access by supporting multiple credential types, including Managed Identity, Service Principal, and Azure CLI. Features like DefaultAzureCredential allow seamless authentication across local environments, CI/CD pipelines, and various Azure cloud deployments.

A comprehensive SDK providing robust authentication credentials for Python applications interacting with Azure services. It simplifies secure access by supporting multiple credential types, including Managed Identity, Service Principal, and Azure CLI. Features like DefaultAzureCredential allow seamless authentication across local environments, CI/CD pipelines, and various Azure cloud deployments.

This is the Azure Resource Manager SDK for .NET, designed to streamline the deployment and management of Weights & Biases (W&B) ML experiment tracking instances directly through Azure Marketplace. It allows developers to programmatically create, configure, and manage W&B environments, including setting up marketplace details, managing admin users, configuring Single Sign-On (SSO), and ensuring robust ML observability within an Azure ecosystem. Ideal for MLOps pipelines.

This is the Azure Resource Manager SDK for .NET, designed to streamline the deployment and management of Weights & Biases (W&B) ML experiment tracking instances directly through Azure Marketplace. It allows developers to programmatically create, configure, and manage W&B environments, including setting up marketplace details, managing admin users, configuring Single Sign-On (SSO), and ensuring robust ML observability within an Azure ecosystem. Ideal for MLOps pipelines.

A comprehensive SDK for running Playwright end-to-end tests at scale. It leverages cloud-hosted browsers within the Azure ecosystem, allowing developers to execute reliable, large-scale automated tests. Features include integrated Azure portal reporting, seamless authentication using Microsoft Entra ID, and strong support for CI/CD pipelines.

A comprehensive SDK for running Playwright end-to-end tests at scale. It leverages cloud-hosted browsers within the Azure ecosystem, allowing developers to execute reliable, large-scale automated tests. Features include integrated Azure portal reporting, seamless authentication using Microsoft Entra ID, and strong support for CI/CD pipelines.

Automates Azure ML Deployer workflows by offering best-practice guidance, code/config generation, and validation for serving, MLOps pipelines, monitoring, and production optimization.

Automates Azure ML Deployer workflows by offering best-practice guidance, code/config generation, and validation for serving, MLOps pipelines, monitoring, and production optimization.