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Best Practices for Analyzing Business Data Using Predictive Analytics

Make sound business decisions with advanced science data. Understand the necessary steps you must take in order to begin with predictive analytics.

Predictive analytics and data science have become go-to approaches to advanced analytics analyses and decision making with organizations. However, many organizations have little to no experience with these techniques within their organization to build predictive models or assess capabilities of consultants or potential hires. This topic helps the persons responsible for defining your predictive analytics strategy understand the key steps and considerations for typical predictive analytics projects without resorting to buzz-words. High-level concepts and some deep-dive ideas will be explained in ways that business stakeholders and analysts can understand.


Runtime: 64 minutes
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Over 30 years and 1.4 million customers worth of experience providing continuing education. Our passion is providing you world-class training to help you succeed in business and as a professional.

Agenda

Have a Framework for the Project

  • Defining Predictive Analytics
  • Introduction to CRISP-DM

Select the Right Problem to Solve

  • How to Choose the Target Variable
  • Principles in Selecting the Data

Don't Skimp on Data Preparation

  • Big 3 Data Prep Steps
  • Principles of Feature Creation

Know the Strengths and Weaknesses of Algorithms

  • The Big 3 Algorithms
  • What to Believe and Distrust About Predictive Models

Assess Your Models With the Right Metric

Conclusion and Summary

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Why Lorman?

Over 30 years and 1.4 million customers worth of experience providing continuing education. Our passion is providing you world-class training to help you succeed in business and as a professional.

Credits

OnDemand Webinar

This program format does NOT qualify, nor meet the National Standard for NASBA accreditation.

Audio & Reference Manual

This program format does NOT qualify, nor meet the National Standard for NASBA accreditation.

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Why Lorman?

Over 30 years and 1.4 million customers worth of experience providing continuing education. Our passion is providing you world-class training to help you succeed in business and as a professional.

Faculty

Dean Abbott

Dean Abbott

Abbott Analytics

  • Co-founder and chief data scientist of SmarterHQ, and President of Abbott Analytics, Inc. in San Diego, California
  • Internationally recognized data mining and predictive analytics expert with over two decades of experience applying advanced data mining algorithms, data preparation techniques, and data visualization methods to real-world problems, including fraud detection, risk modeling, text mining, personality assessment, response modeling, survey analysis, planned giving, and predictive toxicology
  • Wrote, Applied Predictive Analytics, Wiley, 2014; and co-wrote, IBM SPSS Modeler Cookbook, Packt Publishing, 2013
  • Highly-regarded and popular speaker at Predictive Analytics and Data Mining conferences and meetups, and is on the advisory boards for the UC/Irvine Predictive Analytics Certificate as well as the UCSD Data Mining Certificate programs
  • Served several times on the program committee for the KDD Conference Industrial Track
  • B.S. degree in mathematics of computation, Rensselaer; master of applied mathematics degree, University of Virginia
  • Can be contacted at [email protected] or Twitter®: @deanabb
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Over 30 years and 1.4 million customers worth of experience providing continuing education. Our passion is providing you world-class training to help you succeed in business and as a professional.

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Product ID: 391863
Published 2015
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