4 Data Mining Techniques for Businesses (That Everyone Should Know)

4 Data Mining Techniques for Businesses (That Everyone Should Know)

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WpMetadataNoticeÚltima publicación mié, mar 27, 2019
Data Mining is an important analytic process designed to explore data. Much like the real-life process of mining diamonds or gold from the earth, the most important task in data mining is to extract non-trivial nuggets from large amounts of data. Extracting important knowledge from a mass of data can be crucial, sometimes essential, for the next phase in the analysis: the modeling. Many assumptions and hypotheses will be drawn from your models, so it's incredibly important to spend appropriate time "massaging" the data, extracting important information before moving forward with the modeling.
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The year is 2040 and Eric Roberts hates technology. In an era where automated systems and A.I. robots carry out most work obligations, these advancements have rendered scores of humans societally useless. Aimlessly wandering about, the displaced people struggle with their new reality-a hardship painfully familiar to Eric. Once a neuropsychologist, his professional livelihood unceremoniously ended when medical tech forced him into obsolescence. Now a community therapist, he spends his days working with the displaced, helping them craft meaning in a world that no longer needs them. Then Eric's world upends when Arvin-an A.I. robot-arrives at the counseling center for mental health services. Reluctantly, Eric has to work with the embodiment of his misery, and while doing so, unearths a damning secret. With his life at a low point, he figures there's no harm in shelving his professional obligations and investigating the mystery. However, he quickly finds out that solving the unknown will only be possible with help from a most unlikely source.

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