Get to grips with constructing state of the art simulation models with python.
This book is a comprehensive guide to understand various computational statistical simulations using Python.
This book will start with the required foundation to understand various methods and techniques to delve into complex topics. Developers working with simulation models will be able to put their knowledge to work with this practical guide. The book provides a hands-on approach to implementation and associated methodologies that will have you up-and-running, and productive in no time.
Complete with step-by-step explanations of essential concepts, practical examples and self-assessment questions, you will begin by exploring the numerical simulation algorithms, including an overview of relevant applications. You’ll learn how to use Python to develop simulation model and understand how to use the several Python packages. You will then explore various numerical simulation algorithms and concepts, such as Markov Decision Process, Monte Carlo methods, and bootstrapping techniques. By the end of this book, you will be able to construct simulation models.
This book is for Data Scientists, simulation engineers, or anyone who is already familiar with the basic computational methods but now wants to implement various simulation techniques such as Monte-Carlo methods, statistical simulation using Python.
