Data Science

Take your machine learning models to production with new MLOps capabilities

9 мая 2019 г.

At Microsoft Build 2019 we announced MLOps capabilities in Azure Machine Learning service. MLOps, also known as DevOps for machine learning, is the practice of collaboration and communication between data scientists and DevOps professionals to help manage the production of the machine learning (ML) lifecycle.

Senior Program Manager, Azure MLOps

Analytics in Azure remains unmatched with new innovations

6 мая 2019 г.

Digital disruption has created unlimited potential for companies to embrace data as a competitive advantage for their business. As a result, analytics continues to be a key priority for enterprises. When it comes to analytics, customers tell us that they need a solution that provides them with the best price, performance, security, and privacy, as well as a system that can easily deliver powerful insights across the organization. Azure has them covered.

Corporate Vice President, Azure Data

Understanding HDInsight Spark jobs and data through visualizations in the Jupyter Notebook

29 апреля 2019 г.

The Jupyter Notebook on HDInsight Spark clusters is useful when you need to quickly explore data sets, perform trend analysis, or try different machine learning models. Not being able to track the status of Spark jobs and intermediate data can make it difficult for data scientists to monitor and optimize what they are doing inside the Jupyter Notebook.

Senior Program Manager, Big Data Team

Microsoft and NVIDIA bring GPU-accelerated machine learning to more developers

20 марта 2019 г.

With ever-increasing data volume and latency requirements, GPUs have become an indispensable tool for doing machine learning (ML) at scale. This week, we are excited to announce two integrations that Microsoft and NVIDIA have built together to unlock industry-leading GPU acceleration for more developers and data scientists.

Principal Program Manager (Machine Learning Platform)