Applied Math with Python

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 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. This book 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 to create useful customer segments, model revenue growth, and allocate limited resources in product launches or expansions. Inside the book: • Modular, plug-and-play strategies for solving hard problems in Python in situations where a spreadsheet is inadequate • Instructions for building effective, scalable Python scripts incorporating many of the most powerful Python libraries, including pandas, NumPy, matplotlib, seaborn, scikit-learn, and Plotly • Start-to-finish coverage for business professionals – from building a Python scripting environment on your local computer or in a cloud environment to designing, writing, testing, and running a functional script Perfect for entrepreneurs, analysts, managers, and professionals working in AI, data science, and finance, this guide transforms abstract mathematical concepts into useful, repeatable, scalable solutions you can implement immediately in your team and organization.