Azure AI/ML Service
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An Azure AI/ML Service is a cloud-based AI/ML service that is an Azure service.
- Example(s):
- See: GCP Vertex AI, AWS Sagemaker.
Referneces
2023
- chat
- Azure AI is a set of artificial intelligence (AI) and machine learning (ML) services provided by Microsoft Azure, which is a cloud computing platform. Azure AI aims to help developers and data scientists build, deploy, and manage AI solutions using a variety of tools, frameworks, and services. These services include pre-built AI capabilities, machine learning tools, and custom AI development platforms.
- Azure Machine Learning is a specific service within Azure AI that focuses on providing tools, services, and platforms to build, train, and deploy machine learning models. It offers a cloud-based environment that enables developers and data scientists to collaboratively work on model development, testing, and deployment. Some key features of Azure Machine Learning include:
- Drag-and-drop designer: A visual interface for building, training, and deploying machine learning models without the need for coding.
- Automated machine learning: A feature that automates the process of selecting the best algorithm, data preprocessing, and hyperparameter tuning for a given problem, thus reducing the time and effort required for model development.
- MLOps (Machine Learning Operations): Tools and services to manage the end-to-end machine learning lifecycle, including model versioning, monitoring, and deployment.
- Integration with popular open-source frameworks and tools: Azure Machine Learning supports popular ML frameworks like TensorFlow, PyTorch, and Scikit-learn, and integrates with tools like Jupyter notebooks for a seamless development experience.
- Scalable compute resources: Azure Machine Learning allows you to leverage the power of the cloud to train and deploy models on demand, using GPU and CPU clusters.
2023
- https://azure.microsoft.com/en-us/solutions/ai/#overview
- Azure AI — a portfolio of artificial intelligence (AI) services designed for developers and data scientists — to do more with less. Take advantage of the decades of breakthrough research, responsible AI practices, and flexibility that Azure AI offers to build and deploy your own AI solutions. Access high-quality vision, speech, language, and decision-making AI models through simple API calls, and create your own machine learning models using an AI supercomputing infrastructure, familiar tools like Jupyter Notebooks and Visual Studio Code, and open-source frameworks like TensorFlow and PyTorch—all backed by Microsoft's responsible AI principles.
- Azure Applied AI Services: Specialized AI services for specific business scenarios
- Azure Cognitive Services: A comprehensive family of customizable cognitive APIs for vision, speech, language, and decision making
- Azure ML Services: An end-to-end platform for building, training, and deploying machine learning models
- Azure AI Infrastructure: A purpose-built AI supercomputing infrastructure for accelerating innovation
- Azure AI — a portfolio of artificial intelligence (AI) services designed for developers and data scientists — to do more with less. Take advantage of the decades of breakthrough research, responsible AI practices, and flexibility that Azure AI offers to build and deploy your own AI solutions. Access high-quality vision, speech, language, and decision-making AI models through simple API calls, and create your own machine learning models using an AI supercomputing infrastructure, familiar tools like Jupyter Notebooks and Visual Studio Code, and open-source frameworks like TensorFlow and PyTorch—all backed by Microsoft's responsible AI principles.