Читать книгу Fundamentals and Methods of Machine and Deep Learning - Pradeep Singh - Страница 13

The historical background of machine learning (ML), in the same way as other artificial intelligence (AI) concepts, started with apparently encouraging works during the 1950s and 1960s, trailed by a significant stretch of accumulation of information known as the “winter of AI” [9]. As of now, there has been an explosive concern essentially in the field related to deep learning. The start of the primary decade of the 21st century ended up being a defining moment throughout the entire existence of ML, and this is clarified by the three simultaneous patterns, which together gave an observable synergetic impact. The first pattern is big data and the second one is the reduction in the expense of equal processing and memory, and the third pattern is acquiring and building up the possibility of perceptron using deep learning algorithms. The investigation of ML has developed from the actions of a modest bunch of engineers investigating whether a machine could figure out how to solve the problem and impersonate the human mind, and a field of insights that generally overlooked computational reviews, to a wide control that has delivered basic measurable computational hypotheses of learning measures.