Skill UI

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.

This is a high-level Software Development Kit (SDK) designed for managing the full lifecycle of AI projects within Azure AI Foundry. Built for Java, it provides robust client interfaces for core AI operations, including managing connections to Azure resources, uploading and managing datasets, creating and updating search indexes, running model evaluations, and handling deployments. It streamlines complex AI workflow orchestration.

This is a high-level Software Development Kit (SDK) designed for managing the full lifecycle of AI projects within Azure AI Foundry. Built for Java, it provides robust client interfaces for core AI operations, including managing connections to Azure resources, uploading and managing datasets, creating and updating search indexes, running model evaluations, and handling deployments. It streamlines complex AI workflow orchestration.

A comprehensive SDK for building real-time, bidirectional voice AI applications using Azure AI services within the .NET framework. This library facilitates seamless voice interactions, supporting WebSocket communication, advanced features like function calling, and handling audio/text streaming events for developing sophisticated virtual assistants.

This guide provides comprehensive examples for developing real-time chat applications using the Azure Communication Services Chat SDK in Java. It covers essential features including creating chat threads, sending diverse message types (text, HTML), listing message history, managing participants, and handling advanced functionalities like read receipts, message updates, and participant management. Ideal for building robust, enterprise-grade messaging systems.

This guide provides comprehensive examples for developing real-time chat applications using the Azure Communication Services Chat SDK in Java. It covers essential features including creating chat threads, sending diverse message types (text, HTML), listing message history, managing participants, and handling advanced functionalities like read receipts, message updates, and participant management. Ideal for building robust, enterprise-grade messaging systems.

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 .NET SDK for managing Arize AI Observability and Evaluation resources within Azure Resource Manager (ARM). It provides programmatic access to create, read, update, and delete AI organization resources. It is essential for MLOps professionals and developers who need to monitor, track, and evaluate the performance of AI models deployed on Azure.

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.