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Delivering on the Promise of AI / ML: The Emergence of MLOps

In a bygone age, we looked to the future and imagined a world driven by artificial intelligence and machine learning. Through the power of AI and ML, processes would become more efficient, business decisions made more intelligently, and deep analytical insights would be available at the touch of a button.

Today, the future is here.

AI and ML have impacted the global enterprise profoundly: Research from Gartner found that 91% of firms are continually investing in AI / ML. However, further research shows that 85% of machine learning (ML) projects fail, likely because the requirements for running sustained programs are complex and scaling early AI / ML success is a challenge in and of itself.

Enter MLOps.

Building on the framework of DevOps, MLOps allows predictions to be served in real-time with tools that can lower the costs of innovation.

Fill out the form and discover how your organization can harness the true potential of your AI / ML projects through the power of MLOps.

Download the White Paper Now!

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Defining MLOps

Gain a clear understanding of what MLOps is (and how it differs from DevOps).

 

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Assessing Your Current ML Efforts

Uncover the 10-step process to assessing the state of your existing ML projects and how they can achieve desired outcomes.

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Identifying Challenges to MLOps Success

Ensure your MLOps plan is a success by navigating these potential hurdles.

“To grow and succeed to the greatest extent possible, the practice of ML must mature and this hinges largely on the development of MLOps capabilities.”