Applied AI & Advanced Machine Learning
According to Gartner’s analytics, in advanced machine learning, deep neural nets (DNNs) move beyond classic computing and information management to create systems that can autonomously learn to perceive the world, on their own. The explosion of data sources and complexity of information makes manual classification and analysis infeasible and uneconomic. DNNs automate these tasks and make it possible to address key challenges related to the information of everything trend.
DNNs (an advanced form of machine learning particularly applicable to large, complex datasets) is what makes smart machines appear “intelligent.” DNNs enable hardware- or software-based machines to learn for themselves all the features in their environment, from the finest details to broad sweeping abstract classes of content. This area is evolving quickly, and organizations must assess how they can apply these technologies to gain competitive advantage.
Ubiquitous embedded intelligence combined with pervasive analytics will drive the development of systems that are alert to their surroundings and able to respond appropriately.
- Using of Artificial Intelligence in civil aviation
- Machine learning in e-commerce – practice of using and pitfalls
- Machine learning approach to EOR research