For quite some time now, data scientists and machine and deep learning (ML/DL) experts are using different techniques to automate triaging and analysis of tickets in various hi-tech sectors.
Machine Learning, or ML as we call it, is not a new entity. Often, ML and Artificial Intelligence (or AI) are used interchangeably as if they are the same terms. But that’s not the case. You’ll see why through this discerning InfoBlog.
These techniques help in the understanding of the disease as well as initiation and evaluation of ongoing treatment. Apart from this, the dataset of these images is used in further analysis of such diseases occurring around the world as a whole.
Anomaly simply means something unusual or abnormal. We often encounter anomalies in our daily life. It can be suspicious activities of an end-user on a network or malfunctioning of equipment. Sometimes it is vital to detect such anomalies to prevent a disaster.
Machine learning is about using data to build intelligent artefacts that learn over time. It involves collecting and analysing large amounts of data to extract information using various computational structures and algorithms.
Physical servers and storage equipment are a data center reality. How can we ensure that the workloads are distributed correctly across this infrastructure?AI and Machine Learning can come to the rescue here as well. With these technologies, data centers can distribute workloads equally and efficiently across these servers.
Simple explanations of Machine Learning and Artificial Intelligence, and how they’re related... but not at all the same thing.
This article talks about how Kubernetes has emerged from container orchestration platform to manage complex workloads in AI and Machine Learning Stacks, Managing containers in NFV architecture and handling hardware GPU resources.
Infographic on Gartner's tech trends 2019
Author interviewed the CTO of Edge Intelligence firm Swim.ai, Simon Crosby. A discussion was about what are the basics of Edge computing, how analytics helps in making ecosystems intelligent to respond to events, how storage will get revolutionized, how upcoming 5G network features will have impact on edge intelliegence, etc