Machine Learning, machines learning tasks without human intervention. This is sometimes, in modern situations implemented through Deep Learning of which there are several types. In other situations it may be implemented through statistics (for example regression or classification). Deep Learning is the use of algorithms to create Artificial Neural Networks. An artificial neural network is akin to the vast network of neurons in a brain.
The purpose of all Artificial intelligence (AI) in the enterprise is essentially boiled down to either, a) remove rote tasks from humans so that they can focus on the higher value tasks, or to b) undertake calculations at scale that a human cannot, in order to make predictions or take prescriptive actions.
Various experiments already exist within the University. The TechLab is currently piloting 3 of the most common models for Neural Networking, in order to assess their readiness for the University. Additional testing and socialising is needed in order for the University to realise the potential of the platforms.
It's possible to quickly and automatically produce models that can analyze bigger, more complex data and deliver faster, more accurate results – even on a very large scale. By using algorithms to build models that uncover connections, organizations can make better decisions without human intervention. And by building precise models, an organization has a better chance of identifying profitable opportunities – or avoiding unknown risks.