A step-by-step guide for using Python to transform abstract mathematical concepts into effective, on-the-ground scripts that solve real-world business problems
Applied Math with Python: Solve Real-World Problems with Python-Based Solutions is a detailed, step-by-step guide for business professionals, analysts, and data scientists interested in using Python to perform crucial organizational tasks: optimizing inefficient supply chains, calculating probabilities, forecasting financial performance, mining customer data for new insights, and more.
Author, researcher, and Assistant Professor of Finance at the University of North Florida, Blake Rayfield uses practical examples and hands-on exercises to explain how to combine concepts from optimization, probability, statistics, and other branches of mathematics with the Python language to solve difficult, common business problems. You’ll discover how marketing managers can use Python to create useful customer segments, how to model revenue growth, and how to allocate limited resources in a product launch or expansion.
Inside the book:
Perfect for entrepreneurs, analysts, managers, and professionals working in AI, data science, and finance, Applied Math with Python is an expert guide for transforming abstract mathematical concepts into useful, repeatable, scalable solutions you can put to work immediately in your team and in your organization.
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BLAKE RAYFIELD, PhD, is an Assistant Professor of Finance at the University of North Florida. He's a Fulbright Specialist with expertise in applying mathematical solutions to common, difficult business problems. His research has appeared in the Journal of Financial Research, the Quarterly Review of Economics and Finance, and the Review of Behavioral Finance.
Transform mathematical concepts into working Python code for real-world analysis
In Applied Math with Python, Blake Rayfield delivers a detailed and step-by-step guide for business professionals, analysts, and data scientists looking for effective solutions to common business problems: inefficient supply chains, inaccurate probability calculations, uncertain financial projections, disorganized and unused customer data, and more.
The book explains how to use strategies drawn from optimization, probability, statistics, and other branches of mathematics to create scalable and effective solutions to the kinds of operational problems faced by organizations across industries. You?ll find accurate guidance for building Python-powered scripts you can implement whenever ad-hoc, spreadsheet-based techniques no longer work.
Applied Math with Python offers advice for technical and business professionals who want to:
This solutions manual translates abstract mathematical concepts into tested, adaptable code and real-world results for successful teams.
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