This epsisode of the AI Show talks about the new ML assisted data labeling capability in Azure Machine Learning Studio.

You can create a data labeling project and either label the data yourself, or take help of other domain experts to create labels for you. Multiple labelers can use browser based labeling tools and work in parallel.

As human labelers create labels, an ML model is trained in the background and its output is used to accelerate the data labeling workflow in various ways such as active learning, task clustering, and pre-labeling. Finally, you can export the labels in different formats.

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Azure Machine Learning now offers two editions that are tailored for your machine learning needs, Enterprise and Basic, making it easy for developers and data scientists to accelerate the end to end machine learning lifecycle. The Basic edition is a one stop destination for open source developers and data scientists who are comfortable with a code first experience. The Enterprise edition boosts productivity with no-code machine learning tools for all ML skill levels, and is tailored for enterprises of various sizes, developers, data engineers or data workers.

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Leila Etaati, a Data Soup Summit speaker,  will be in the USA for a month and presenting a one day workshop at the following locations