Data Analysis Tools for Neural Data Cognitive Computing: Neural-Inspired Algorithms

Data Analysis Tools for Neural Data Cognitive Computing: Neural-Inspired Algorithms

Shiddarth Srivastava (Ajay Kumar Garg Engineering College, India) and Rashmi Sharma (Ajay Kumar Garg Engineering College, India)
DOI: 10.4018/978-1-6684-6980-4.ch009
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Abstract

The ability to draw conclusions and take action from data hasn't altered all that much despite significant technological developments in recent years. Applications are still typically created to carry out predefined tasks or automate business procedures; therefore, the logic must be coded to account for all possible usage scenarios. They do not grow from their mistakes or adjust to changes in the data. Although they are cheaper and faster, computers aren't substantially smarter. Of course, people now aren't all that much brighter than they were in the past. For both humans and machines, that is about to change. The old notion of computing as process automation is being replaced by a new generation of information systems that offer a collaborative platform for discovery. These systems' initial wave has already improved human cognition in a number of areas.
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What Is Big Data?

Large data sets that are too big to manage and analyse using conventional data processing tools are frequently referred to as “big data.” Looking for hints on the Web reveals an almost universal definition that most people supporting the Big Data ideology agree upon, which can be summed up as follows: Big Data describes a situation in which data sets have grown so large that traditional information technologies can no longer effectively manage their size, scale, or growth (T. Nam et al.,2011). In other words, the data set has gotten so big that managing it and extracting value from it are both challenging. The primary difficulties are the acquisition, storage, searching, sharing, analytics, and visualization of data A. P. Appel et al., 2017).

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