Table 1.

Glossary of terminologies used in Artificial intelligence.

Terminology	Description
Machine Learning (ML)	The process by which an algorithm encodes statistical regularities inherent in a database of examples, into parameter weights for future predictions
Supervised Learning	Training a machine learning algorithm by means of previously expert labelled training examples.
Unsupervised Learning	When machine learning algorithm discovers hidden patterns or data groupings without the need for human intervention.
Model	A trained machine learning algorithm, ready to make predictions from unseen data.
Training	Feeding a machine learning algorithm with examples from a training dataset so that it can derive useful parameters for future predictions.
Artificial Neural Network	A machine learning technique that processes information in an architecture comprising of a large number of layers, each layer extracting desired parameters incrementally from training data.
Deep Neural Network (DNN)	A deep learning architecture with multiple layers between input and output layers.
Convolutional Neural Network (CNN)	A class of DNN that display connectivity patterns that are analogous to that of the connectivity patterns and image processing in visual cortex.
Black Box	Human inability to explain the precise steps leading to the model's predictions, due to complex maze of parameters that is inscrutable to humans.