Data Mining And Machine Learning

1631 Words Nov 14th, 2014 7 Pages
Introduction
Nowadays, data mining and machine learning become rapidly growing topics in both industry and academic areas. Companies, government laborites and top universities are all contributing in knowledge discovery of pattern recognition, text categorization, data clustering, classification prediction and more. In general, data mining is the technique used to analyze data from multi perspectives and reveal the hidden gem behind the enormous amount of data. With the explosive growth of data collections, it becomes time-consuming less effective to extract valuable information from massive databases through the use of traditional data analysis methods. An alternative way to solve this problem is to apply data mining, given considerations of its powerful, beneficial and scalable applications. Therefore, this paper will discuss two potential problems of predictability and scalability with traditional data analysis method and solutions provided by advanced data mining technologies, followed by discussion of other innovative technologies that stem from data mining.
Problem
In recent decades, Internet, data storage and hardware capacity have experienced rapid development. Along with these influential changes, data science/mining becomes a great concern in both industry and academic field. According to an article from The Economist, companies are producing an unimaginably amount of data at rapid pace. Walmart deals with more than 1 million transactions every hour, and 2.5…

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