Computational Business Analytics (Chapman & Hall/CRC Data by Subrata Das

By Subrata Das

Learn how one can accurately Use the most recent Analytics ways on your Organization


Computational enterprise Analytics offers instruments and methods for descriptive, predictive, and prescriptive analytics appropriate throughout a number of domain names. via many examples and demanding case experiences from quite a few fields, practitioners simply see the connections to their very own difficulties and will then formulate their very own answer strategies.



The booklet first covers center descriptive and inferential records for analytics. the writer then complements numerical statistical recommendations with symbolic synthetic intelligence (AI) and computing device studying (ML) strategies for richer predictive and prescriptive analytics. With a different emphasis on equipment that deal with time and textual information, the text:





  • Enriches vital part and issue analyses with subspace tools, akin to latent semantic analyses

  • Combines regression analyses with probabilistic graphical modeling, similar to Bayesian networks

  • Extends autoregression and survival research strategies with the Kalman clear out, hidden Markov versions, and dynamic Bayesian networks

  • Embeds choice timber inside effect diagrams

  • Augments nearest-neighbor and k-means clustering options with aid vector machines and neural networks



These methods aren't replacements of conventional statistics-based analytics; quite, more often than not, a generalized procedure might be decreased to the underlying conventional base procedure less than very restrictive stipulations. The ebook indicates how those enriched suggestions provide effective ideas in components, together with consumer segmentation, churn prediction, credits hazard evaluation, fraud detection, and advertisements campaigns.

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