Microsoft Azure Machine Learning Helps Organizations Automate Machine Learning


Machine learning is an integral part of today’s business world. However, if your organization doesn’t have the in-house personnel to tackle this intimidating essential, your employees can get overwhelmed in a hurry. Once again, Microsoft Azure has a solution to help its users make sense of the massive amount of data it produces to gain better insights into its machine learning.  Microsoft Azure Machine Learning Helps Organizations Automate Machine Learning.

Azure Machine Learning is an enterprise-grade machine learning service used to build and deploy models with machine learning operations (MLOps) capabilities to streamline the machine learning lifecycle and help automate it. It provides deep integration with Azure Synapse Analytics, a limitless analytics service that brings together data integration, enterprise data warehousing and big data engineers and data scientists, allowing them to build models with ease, enrich the enterprise data, and create even greater outcomes with their data.  

MLOps – also known as DevOps for machine learning – enables data science and IT teams to collaborate and increase the pace of model development and deployment via monitoring, validation and governance of machine learning models.  

Azure Machine Learning helps users rapidly build and deploy these robust machine learning models using tools that meet your organization’s needs regardless of skill level. Use built-in Jupyter Notebooks with IntelliSense or the drag-and-drop design. Accelerate model creation with automated machine learning, and access powerful feature engineering, algorithm selection, and hyperparameter-sweeping capabilities. Increase team efficiency with shared datasets, notebooks, models and customizable dashboards that track all aspects of the machine learning process.  

You can also access state-of-the-art responsible machine learning capabilities to understand, control and help protect your data, models and processes. Explain model behavior during training and inferencing and build for fairness by detecting and mitigating model bias. Preserve data privacy throughout the machine learning lifecycle with differential privacy techniques and use confidential computing to secure machine learning assets. Automatically maintain audit trails, track lineage and use model datasheets to enable accountability.  

With seamless integration and advanced capabilities, Azure Machine Learning and Azure Synapse Analytics make it easier for organizations to build a machine learning practice to achieve their business objectives. And organizations can accelerate their success by augmenting analytics with machine learning through a multistage maturity approach.  

2W Tech is a technology service provider and Microsoft Gold Partner. Give us a call today to learn more about how Microsoft is using modern technologies like machine learning to help businesses thrive in the digital transformation. 

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