Classification predictive output is a label and for regression its a quantity. Generative algorithms can also be used as classifiers. It just so happens that they can do more than categorising the input data. Can call classification as sorting and regression as connecting technique as well.
AILabPage defines Deep learning is “Undeniably a mind-blowing synchronisation technique applied on data with computing power, skills and experience which practically has no limits“.
Unsupervised learning helps to find a hidden jewel in data by grouping similar things together. Data have no target attribute. The algorithm takes training examples as the set of attributes/features alone. In this post, I have summarised my whole upcoming book “Unsupervised Learning – The Unlabelled Data Treasure” on one […]
ML instructs an algorithm to learn for itself by analysing data. Algorithms here learn a mapping of input to output, detection of patterns or by reward. The more data it processes, the smarter the algorithm gets.
Artificial Neural Networks – As the name suggest “Neural Network”, they are inspired by the human brain system. As ANNs were originally designed with biological neurons as a reference point thus sometimes they are called as a brain model for computers. It’s more of a framework than an […]