Azure Machine Learning (AML) is a cloud-based machine learning service from Microsoft to help you better manage MLOps and accelerate the machine learning project lifecycle. ML professionals, data scientists, and data engineers can use AML in daily workflows to train and deploy models for enhanced production.
Accelerate time to value and deliver responsible machine-learning solutions
Label data and prepare it for data exploration using an analytics engine. Access, create, and share data at scale.
Utilize collaborative Jupyter notebooks and automatically train and tune accurate machine learning models. Use familiar tools like Visual Studio Code and GitHub to switch easily from local to cloud training.
Automate ML workflows by creating pipelines and CI/CD. Optimize machine learning models through accelerated training and interface at lower costs with ONNX Runtime.
Detect drift and maintain the ML model's accuracy. Enjoy continuous monitoring with Azure Security Center. Become better at monitoring and analysis by tracking, logging, and analyzing data, models, and resources.
Let's connect to understand and reveal your business potentials and expansion capabilities with Azure Machine Learning Solutions.
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Most probably, a big Yes. Because it is a hot topic today and will continue to be. In Canada and the United States, Microsoft's ML services are available for 12 regions. In total, ML enthusiasts and data engineers in more than 40 regions across the world can access Azure Machine Learning. Contact Dynamics Square for more information.
The service-level-agreement (SLA) for Microsoft Azure Machine Learning is 99.9 percent.
Azure Machine Learning (AML) studio is a top-notch resource for building machine learning models. It's a unique yet centralized platform for data scientists and developers to show their capabilities in creating the future.