Global organizations are adopting programmable networks as a first step towards network automation, but this can be advanced more quickly with machine learning.
Machine learning applications span a wide variety of use cases, including perceptual tasks such as image search, object and scene recognition and captioning; voice and natural language recognition and generation; self-driving cars and automated assistants such as Siri; as well as various engineering, financial, medical, and scientific applications.
The recent progress of machine learning and deep learning in particular has been nothing short of spectacular. It’s a new area for networking, but one that is growing incredibly fast.
This presentation will provide insight into the intersection of machine learning, networking and DevOps as well as an overview of recent advances in machine learning with an eye toward network applications and next-generation network automation.
This presentation will provide insight into the intersection of machine learning, networking and DevOps as well as an overview of recent advances in machine learning with an eye toward network applications and next-generation network automation.
