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Modern Business Analytics provides the student a detailed overview of business analytics concepts, including linear regression, spatial data, frequentist uncertainty, the bootstrap, out-of-sample performance, model selection, uncertainty quantification for the lasso, nearest neighbors, classification via regression, notation for causal inference, instrumental variables, conditional ignorability, among others. This textbook is direct and concise with systematic content designed to engage today’s student through visually engaging content. There is a wide variety of assignment types that help students master business analytics concepts and build real-world working capability. Modern Business Analytics goes into using time series as controls, causal inference with random forests, clustering, partial least squares, distributed computing for random forests, word embedding, the ingredients of deep learning, stochastic gradient descent, the state of the art, intelligent automation, randomized controlled trials, heterogeneous treatment effects, likelihood and deviance, and multinomial logistic regression. A chapter is broken down into residuals. Buy Modern Business Analytics and be confident in your business analytics education and career.
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