Today, Hewlett Packard Enterprise (HPE) announced a container-based software solution, HPE ML Ops, to support the entire lifecycle of machine learning models for on-premises public and hybrid cloud environments. The new solution features a process similar to DevOps for standardizing machine learning workflows and accelerating the deployment of AI from months to days. Business adoption has more than doubled in the past four years1 and organizations are still investing significant time and resources in creating machine learning and deep learning models for a wide variety of AI use cases, such as fraud detection, personalized medicine, and predictive customer analysis medicine. . However, the biggest challenge that technical professionals face is to implement ML, also known as the “last mile”, to successfully implement and manage these models and unlock business value. According to Gartner, at least 50% of machine learning projects will not be fully implemented until 2021 due to a lack of operations.