Session
What's new with Azure Machine Learning
with Matt Winkler, Bob Strudwick, Naeem Khedarun, Saul Vargas Sandoval
In September, we launched a huge set of updates for Azure Machine Learning to let you manage the end to end lifecycle of Machine Learning Development. We made it easy to scale to the cloud, deploy through containers to the cloud and the edge, use great frameworks like Tensorflow, PyTorch, Scikit, and more, and gave you a great monitoring and management experience. 7 months later, we're back to update you on the next wave of ML capabilities that will be at your fingertips to make it faster to build models, even easier to scale, more deployment options, and a few more things we're pretty excited to share with you. In this session, you'll learn how you can easily use Azure Machine Learning to build and deploy models for any of your applications.
Create a Free Account (Azure): https://aka.ms/azft-ml
In September, we launched a huge set of updates for Azure Machine Learning to let you manage the end to end lifecycle of Machine Learning Development. We made it easy to scale to the cloud, deploy through containers to the cloud and the edge, use great frameworks like Tensorflow, PyTorch, Scikit, and more, and gave you a great monitoring and management experience. 7 months later, we're back to update you on the next wave of ML capabilities that will be at your fingertips to make it faster to build models, even easier to scale, more deployment options, and a few more things we're pretty excited to share with you. In this session, you'll learn how you can easily use Azure Machine Learning to build and deploy models for any of your applications.
Create a Free Account (Azure): https://aka.ms/azft-ml
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