Supervised vs Unsupervised Learning - What is the difference? - Latest, Trending Automation News

Machine Learning and Artificial Intelligence are rapidly changing the landscape of how organizations function in the world. From data analysis to make independent decisions based upon past experiences, Machine Learning is being used to help organizations make informed decisions but before any of that happens, the algorithms and associated software have to be trained accordingly. Two methods namely supervised learning and unsupervised learning, are widely used to train AI programs. Supervised Learning can be considered equivalent to teaching a toddler how to walk or so forth. The software will have a dataset as well as corresponding input and output pairs which can form a training model for the software. Linear Regression is an example of Supervised Learning and in this case, regression is used when the output is a real number or quantity, let's say dollars or weights.