Machine Learning (ML)

This introduction to Gartner’s research describes Cisco’s responsible approach to AI with a focus on transparency, security and privacy to protect human rights.

Predictive networks can help mitigate downtime and add to an overall positive customer experience. Learn more benefits and some common misconceptions around predictive networks.

How machine learning applications can be deployed using Cisco Intersight Kubernetes Service, and how to build an automated ML pipeline using Kubeflow.

Want to create your first Machine Learning model?... Build a web-application with Django?... Get started with MLOps & Kubeflow?... Integrate a Meraki MV Cameras and MT Sensors?... Then come get your hands dirty in the DevNet Zone at Cisco Live.

A high level exploration of the potential for machine learning and artificial intelligence systems to impact future service provider networking. The blog outlines a path to that future and recommends getting started by simplifying existing network infrastructures and moving toward a common end-to-end forwarding architecture.

Cisco's Chief Data & Analytics Evangelist, shares 13 lessons she's learned in her 13 years at Cisco as she prepares to take the next step in her career.

Cisco Full Stack Observability (FSO) enhances Artificial Intelligence for IT Operations (AIOps) by consolidating visibility of the technology stack across operational domains and extracting insights from the vast amounts of operational data—allowing you to quickly remediate issues, optimize infrastructure, and keep your operational transformation on track.

Learn how MLOps can add efficiency and predictability to the design, build phase, deployment, and maintenance of machine learning models, and help to automate machine learning workflows.

MLOps framework helps in accelerating ML/AI deployments conveniently at scale ensuring improved data security and enhanced model accuracy.