As machine learning models are put into production and used to make critical business decisions, the primary challenge becomes operation and management of multiple models. Machine learning operations (MLOps) is the technical response to that issue, helping companies to manage, monitor, deploy, and govern their models from a central hub.
Our report, The Business Value of MLOps by Thomas Davenport, highlights some of the most impactful benefits of MLOps tools and processes for different types of organizations. It is based on interviews with MLOps user companies and several MLOps experts.
Download the report to find out:
- How enterprises in various industries are using MLOps capabilities
- Which organizational challenges affect MLOps implementations
- How to determine the benefits of an MLOps infrastructure
DataRobot's platform makes my work exciting, my job fun, and the results more accurate and timely – it's almost like magic!
I think we need to take it upon ourselves in the industry to build the predictive models that understand what the needs and wants of our customers are, and go through the whole curation process, become their concierge.
At LendingTree, we recognize that data is at the core of our business strategy to deliver an exceptional, personalized customer experience. DataRobot transforms the economics of extracting value from this resource.
We know part of the science and the heavy lifting are intrinsic to the DataRobot technology. Prior to working with DataRobot, the modeling process was more hands-on. Now, the platform has optimized and automated many of the steps, while still leaving us in full control. Without DataRobot, we would need to add two full-time staffers to replace what DataRobot delivers.
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