The following articles help you get started with Azure Machine Learning. Azure Machine Learning v2 REST APIs, Azure CLI extension, and Python SDK are designed to streamline the entire machine learning lifecycle and accelerate production workflows. The links in this article target v2, which is recommended if you're starting a new machine learning project.
Getting startedIn Azure Machine Learning, the workspace is the main resource that organizes and manages everything you create, such as datasets, models, and experiments.
Deploy models for low-latency, real-time machine learning predictions.
Automated ML (AutoML) refers to the process of streamlining machine learning model development by automating its repetitive and time-consuming tasks.
With Azure Machine Learning, you can import data from your local computer or connect to existing cloud storage services.
Use machine learning pipelines to build workflows that connect different stages of the ML process.
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