Operationalize AI in Real Time with Streaming Analytics
The AI Ladder, along with CRISP-DM, provides a strategic approach to creating CI applications on real time
Looks at issues related to artificial intelligence technologies, including cognitive computing, deep learning, and machine learning. Considers also supervised and unsupervised learning and natural language processing.
The AI Ladder, along with CRISP-DM, provides a strategic approach to creating CI applications on real time
Building continuous intelligence applications on cloud-native architectures using containers and Kubernetes makes it easier to deploy, maintain, and update …
Incorporating machine learning capabilities into BI solutions will bring sophisticated analytics to more people, groups, and business
Previously, the way to identify these disorders would be through manual scoring, which is time-consuming and can lead to inaccuracies.
With AI becoming more prevalent, it’s clear that a platform that can manage the complete AI development and production life cycle will become more
In the news this week: a fast in-memory real-time analytics processing platform is now available as a managed service on Google cloud, an orchestrator that …
Deep learning is capable of incredible things, but if you are working with mostly structured data for straightforward purposes, Machine Learning can be a much …
The combination of HCI and edge computing will give AI the tools to evolve to the next level, enabling smarter and faster decision making for
Smart thermostats have been around for a while, but researchers at Swiss federal laboratory Empa have gone one step further, adding machine
AI hardware accelerators have massively parallel architectures that economically deliver the needed compute performance for Continuous Intelligence …