Mark I was enourmous in size, measuring 8 feet high, 51 feet long and three feet deep. It weighed 5 tons, used 530 miles of wire and 730,000 separate parts. The operation of these parts was powered and synchronized by a long horizontal rotating shaft. A four horsepower engine drives the mechanical parts.
Harvard Mark I, an early protocomputer, built during World War II in the United States. While Vannevar Bush was working on analog computing at the Massachusetts Institute of Technology (MIT), across town Harvard University professor Howard Aiken was working with digital devices for calculation. He had begun to realize in hardware something like the 19th-century English inventor Charles Babbage’s Analytical Engine, which he had read about. Starting in 1937, Aiken laid out detailed plans for a series of four calculating machines of increasing sophistication, based on different technologies, from the largely mechanical Mark I to the electronic Mark IV.
It is a computer aided technique of searching and evaluating a bulk of data in order to obtain useful information.
This technique searches through the data to find hidden patterns and uses statistical methods to find relationship among data for finding predictive information and for classification of data.
This is a mixture of different disciplines which include machine learning, statistics and artificial intelligence and also some mathematical methods.
Often the useful information is extracted from enormous database using modeling technique which is used to build a model from instances of the data where the solution is known and later apply this model on the instances where the solution is unknown.
In unsupervised data mining, the data analysis is not done by using modeling technique. In other words the labels are provided in order not draw inferences and prediction from data sets. Example is clustering.
In supervised data mining the model is developed to make inferences and classification. Example is neural networks.
For example data mining is used in Medicine industry to provide more accurate diagnostics and treatments on the basis of patient's medical history , physical examination or different patient tests data.
Data mining also makes it possible to manage health resources more efficiently and cost-effectively by detecting risks, predicting diseases in certain sections of the population or predicting hospitalization duration.
