Download Applied Predictive Analytics: Principles and Techniques for by Dean Abbott PDF

By Dean Abbott

Learn the paintings and technology of predictive analytics — thoughts that get results

Predictive analytics is what interprets monstrous information into significant, usable company details. Written by way of a number one specialist within the box, this consultant examines the technology of the underlying algorithms in addition to the rules and most sensible practices that govern the artwork of predictive analytics. It truly explains the speculation at the back of predictive analytics, teaches the equipment, ideas, and methods for undertaking predictive analytics tasks, and provides assistance and methods which are crucial for winning predictive modeling. Hands-on examples and case reviews are included.

  • The skill to effectively follow predictive analytics permits companies to successfully interpret tremendous facts; crucial for pageant today
  • This advisor teaches not just the foundations of predictive analytics, but additionally how one can follow them to accomplish actual, pragmatic solutions
  • Explains tools, ideas, and methods for accomplishing predictive analytics initiatives from begin to finish
  • Illustrates every one procedure with hands-on examples and comprises as sequence of in-depth case experiences that practice predictive analytics to universal enterprise scenarios
  • A spouse site presents all of the information units used to generate the examples in addition to a loose trial model of software

Applied Predictive Analytics fingers information and enterprise analysts and enterprise managers with the instruments they should interpret and capitalize on gigantic data.

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Additional info for Applied Predictive Analytics: Principles and Techniques for the Professional Data Analyst

Sample text

As in 2006, concerns about privacy were again raised, but this time the mathematics behind the program, while typically described as data mining in the past, was now often described as predictive analytics. Graduate programs in analytics often use both data mining and predictive analytics in their descriptions, even if they brand themselves with one or the other. Who Uses Predictive Analytics? In the 1990s and early 2000s, the use of advanced analytics, referred to as data mining or computational statistics, was relegated to only the most forward-looking companies with deep pockets.

Defining Data for Predictive Modeling Data for predictive modeling must be two-dimensional, comprised of rows and columns. Each row represents what can be called a unit of analysis. For customer analytics, this is typically a customer. For fraud detection, this may be a transaction. For call center analytics, this may refer to an individual call. For survey analysis, this may be a single survey. The unit of analysis is problem-specific and therefore is defined as part of the Business Understanding stage of predictive modeling.

First, predictive analytics is data-driven, meaning that algorithms derive key characteristic of the models from the data itself rather than from assumptions made by the analyst. Put another way, data-driven algorithms induce models from the data. The induction process can include identification of variables to be included in the model, parameters that define the model, weights or coefficients in the model, or model complexity. Second, predictive analytics algorithms automate the process of finding the patterns from the data.

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