“Want to go Digital but where to start?” is a question lot of large businesses are facing. Does one get the data organized first or power an Analytics use case? 592 more words
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Machine learning commonly requires the use of highly unbalanced data. When detecting fraud or isolating manufacturing defects, for example, the target event is extremely rare – often way below 1 percent. 264 more words
When building models, data scientists and statisticians often talk about penalty, regularization and shrinkage. What do these terms mean and why are they important?
According to Wikipedia, regularization “refers to a process of introducing additional information in order to solve an ill-posed problem or to prevent overfitting. 944 more words
One way to assess the precision of a statistic (a point estimate) is to compute the standard error, which is the standard deviation of the statistic’s sampling distribution. 1,352 more words
Citizens served by the government are increasingly the same digital savvy consumers that market disruptors in banking, retail and utilities are attracting with sophisticated, data-driven online experiences. 430 more words