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Analytical Thinking for AI and Data Science: Asking the Right Questions by Daniel Vaughan

Analytical Thinking for AI and Data Science: Asking the Right Questions

by Daniel Vaughan
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Book cover type: Paperback
  • ISBN13: 9781492060949
  • Binding: Paperback
  • Subject: N/A
  • Publisher: O'Reilly Media
  • Publisher Imprint: O'Reilly Media
  • Publication Date:
  • Pages: 275
  • Original Price: USD 79.99
  • Language: English
  • Edition: N/A
  • Item Weight: 363 grams
  • BISAC Subject(s): Information Theory, Artificial Intelligence / General, and Business & Productivity Software / Business Intelligence

While several market-leading companies have successfully transformed their business models by following data- and AI-driven paths, the vast majority have yet to reap the benefits. How can your business and analytics units gain a competitive advantage by capturing the full potential of this predictive revolution? This practical guide presents a battle-tested end-to-end method to help you translate business decisions into tractable prescriptive solutions using data and AI as fundamental inputs.

Author Daniel Vaughan shows data scientists, analytics practitioners, and others interested in using AI to transform their businesses not only how to ask the right questions but also how to generate value using modern AI technologies and decision-making principles. You'll explore several use cases common to many enterprises, complete with examples you can apply when working to solve your own issues.

  • Break business decisions into stages that can be tackled using different skills from the analytical toolbox
  • Identify and embrace uncertainty in decision making and protect against common human biases
  • Customize optimal decisions to different customers using predictive and prescriptive methods and technologies
  • Ask business questions that create high value through AI- and data-driven technologies

Vaughan, Daniel: - Daniel Vaughan is the data science lead for Airbnb in Latin America. Previously he was Head of Data Science and Chief Data Officer at Telefonica Mexico. He has more than 15 years of experience solving problems using predictive and prescriptive methods.

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