Automated ML is an emerging field in Machine Learning that helps developers and new data scientists with little data science knowledge build Machine Learning models and solutions without understanding the complexity of Learning Algorithm selection, and Hyperparameter tuning. With Azure Machine Learning's automated machine learning capability, given a dataset and a few configuration parameters, you will get a trained high-quality Machine Learning model for the dataset that you can use for Predictions. In this session, you will learn how to use Automated ML for productivity gains, empowering domain experts to build ML-based solutions and scale to build several models with Azure Machine Learning's automated ML.

Instructor's Bio

Aniththa Umamahesan, Program Manager at Microsoft

She is a Program Manager on Microsoft Azure Machine Learning team. Her latest mission is accelerating and democratizing Artificial Intelligence via Automated Machine Learning.

Nikolay Rovinskiy, Software Engineer at Microsoft

He is a Software Developer in the AutoML team. His primary focus is forecasting. The developer of computational biology software with experience in industrial and academic settings, the creator of established software for DNA manipulation and growth curve analysis downloaded 1,833 and 172 times respectively.

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    Machine learning simplified: from ideation to deployment in minutes with automated machine learning

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