Publisher's Synopsis
Reactive Publishing
Data-Driven Decision Making at Scale
Prediction is powerful - but prescription is transformative. In today's data-driven world, the ability to not only forecast outcomes but recommend optimal actions is what separates insight from impact.
Prescriptive Analytics with Python is your hands-on guide to building intelligent decision systems that go beyond analysis - and actively drive strategy, automation, and results. From linear programming and optimization to advanced reinforcement learning frameworks, this book covers the full spectrum of tools used to develop scalable prescriptive solutions.
Inside, you'll learn how to:
Apply optimization techniques like linear, integer, and nonlinear programming
Leverage libraries like PuLP, SciPy, and Pyomo to solve real business problems
Build recommender systems that go beyond prediction to action
Integrate simulation, scenario modeling, and constraint-based decision engines
Combine predictive models with prescriptive logic for smarter automation
Deploy scalable prescriptive solutions in supply chain, finance, marketing, and operations
Whether you're a data scientist, business analyst, or Python developer looking to level up your analytics game, this book gives you the practical knowledge to move from "What will happen?" to "What should we do?"
Think ahead. Decide smarter. Build systems that act.
