Reinforcement Learning (RL) – A more general form of machine learning than supervised learning or unsupervised learning. It learns from interaction with the environment to achieve a goal or simply learns from reward and punishments. This learning is inspired by behaviourism phycology. Reinforcement Learning (RL) – History From the best research, I got […]
Naive Bayes – A classification algorithm under supervised learning group based on probabilistic logic. This is one of the simplest machine learning algorithms of all times. Generative algorithms from GANs are also used as classifiers, interestingly they can do much more than categorisation though. Logistic regression is another classification […]
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.
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.