A rising number of businesses are taking advantage of ML (Machine Learning) to improve efficiency, drive innovation and boost the customer experience. With this increased use of machine learning, customers may also wish to consider the cost-benefit and value analysis across the infrastructure, process and operations within the team and firm.
So, what’s unique about Azure Machine Learning. It is the enterprise-grade service that is used to build and deploy models quicker and speed up the machine learning lifecycle. Customers from all over the world realize the benefits and impacts of the Azure ML.
Benefits of Azure ML:
Azure ML provides progressive machine learning operations (MLOps) abilities for operationalizing the lifecycle. According to a recent search, it was found that after the investment in the Azure ML, customers experienced more efficiencies in their ability to execute the ML projects, achieve lower operational costs and drive more significant revenue.
The main benefits of using the Azure ML are:
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Increase in three-year project ROI of 189% to 335%.
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Improved productivity of the data scientists up to 25% and data engineering productivity up to 40%.
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Up to 40% reduction in time to onboard the new data scientists, which results in reduced costs.
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Increased operational competence by streamlining model development, validation, training, monitoring and deployment.
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Increased time-to-value of ML initiatives and model accuracy that results in improved cost-savings and revenue.
Getting started with the Azure ML is not a challenging task. Since Azure ML is a wholly managed machine learning service that enables firms to build, deploy and manage thousands of models at scale, it helps all types of firms. It mainly offers support from the ground-up for compliance, security, and AI for the data scientists and developers to become more productive and speed up the time-to-value. Get started with Azure by taking the Azure cloud certification training at EkasCloud.
Relevant courses that you may be interested in:
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