5 pillars of an effective AI/ML platform
AI and ML are essential for today’s organizations, and data is just as critical to applications as the code they are built on. But there is still a lack of collaboration between the different groups involved in the development of AI- and ML-driven apps.
To effectively use AI, ML, and data science in deployable applications, companies must bring together developers, IT ops, data engineers, data scientists, and ML engineers to operationalize machine learning operations (MLOps).
In this white paper, you’ll learn about the top 5 considerations you should make for your AI/ML platform. Read on to learn how you can enable your organization to create data-driven apps in a security-focused and collaborative way.