Machine Learning Introduction Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves. It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as email filtering and computer vision, where it is difficult or infeasible to develop conventional algorithms to perform the needed tasks.
History of Machine Learning <1950s- Statistical methods are discovered and refined. 1950s- Pioneering machine learning research is conducted using simple algorithms. 1960s- Bayesian methods are introduced for probabilistic inference in machine learning. 1970s- AI Winter caused by pessimism about machine learning effectiveness. 1980s- The discovery of backpropagation causes a resurgence in machine learning research.