Machine Learning (ML)

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

The use of Artificial Intelligence (AI), when combined with human experiences, has resulted in quick wins for business operations across multiple industries. But the use of smart machines (AI-powered systems) raises numerous ethical concerns. To tackle ethical challenges, AI-powered systems need ethical values built into the model design itself, along with clearly defined success metrics.

Cisco’s Duo Security announces general availability of Duo Trust Monitor, enabling organizations to consistently and continuously monitor the level of trust granted to users via machine-learning and analytics.

Delivering on-premise ML capabilities, with potential hybrid configurations giving data scientists the best of both worlds.

This week, we’ll discuss the three major gaps that prevent enterprise from taking advantage of AI/ML and how to bridge them – with Cisco’s help.

Cisco believes that IT must be intimately involved with the data science projects to ensure that data governance, both on-premise or on-cloud, be properly administered and managed.

Do you know that Kubeflow 1.0 has just been recently released by the Kubeflow Community?  Kubeflow is the open source project integrating TensorFlow, PyTorch and other machine learning capabilities into a cohesive tool, from data ingestion, through machine learning, and even inferencing. 

Data Science Applied In Business Today. In the past decade, there has been an explosion in the application of data science outside of academic realms. The use of general, statistical, predictive machine learning models has achieved high success rates across multiple occupations including finance, marketing, sales, and engineering, as well as multiple industries including entertainment, […]

At Cisco, we have been thinking through what connectivity looks like to the application developer and platform engineer. The cloud-native Network would connect all such service endpoints, and only those endpoints, wherever they happen to be and in whatever form – as modern cloud-native, or traditional monolithic systems.