Technology is growing and changing at such a fast pace, that today’s development and concepts get old by tomorrow!. Code’s or machine’s ability to learn and response without being programmed has become utmost popular and is leading most of the daily process, where least human involvement is required now.
Focusing on the trend of data being generated from ample of processes on day to day basis in organization has lead Machine learning to emphasize more on the development part where programs can be developed to deal with new strains of data from the various processes.
The pace at which the data is being generated from a small process or a bigger process is in equal demand for auto capture of the data from one end and should be analyzed by the system at front end with all possible scales and speculations for quicker decisions by the management. Following this now the trend of the development of algorithms has made shift from writing “supervised algorithms” to unsupervised algorithm, where the supervised part of the algorithm gives better insights into the new data from past data and unsupervised part concludes from the old datasets.
Process Software should be backed by the statistical analysis and predictive analytics to make artificial intelligence and to automate the decisions making ability in process(es).
Though even if organizations and regulatory bodies make standard guidelines for electronic technologies where the ample of codes are being run to capture, store, clean, analyze, and present the result in fractions to the user, will again keep on changing and evolving with growing technology. This process would leave behind the QUESTIONS and SCENARIOS unaddressed!. Manual and Automated testing of the application would not be sufficient to make application stand with data set variation.
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