To train a machine learning model with Azure Machine Learning, you need to make data available and configure the necessary compute. After training your model and tracking model metrics with MLflow,...
Read MoreTo train a machine learning model with Azure Machine Learning, you need to make data available and configure the necessary compute. After training your model and tracking model metrics with MLflow, you can decide to deploy your model to an online endpoint for real-time predictions. Throughout this learning path, you explore how to set up your Azure Machine Learning workspace, after which you train and deploy a machine learning model.
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| Live Virtual | 9:00AM – 5:00PM EDT | |
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Live Virtual |9:00AM – 5:00PM EDT
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Class was very informative, although one lab didnt but will try again later
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had a good time with the course, however some topics were left out due to the compact amount of time for training.
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