Hands-On Simulation Modeling with Python: Develop simulation models for improved

Description: Hands-On Simulation Modeling with Python by Giuseppe Ciaburro Hands-On Simulation Modeling with Python, Second Edition teaches you how to leverage Python to develop simulation models and use various Python packages. The book will help you explore various numerical simulation algorithms and concepts, such as the Markov Decision Process, Monte Carlo methods, and bootstrapping techniques. FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher Description Learn to construct state-of-the-art simulation models with Python and enhance your simulation modelling skills, as well as create and analyze digital prototypes of physical models with easeKey FeaturesUnderstand various statistical and physical simulations to improve systems using PythonLearn to create the numerical prototype of a real model using hands-on examplesEvaluate performance and output results based on how the prototype would work in the real worldBook DescriptionSimulation modelling is an exploration method that aims to imitate physical systems in a virtual environment and retrieve useful statistical inferences from it. The ability to analyze the model as it runs sets simulation modelling apart from other methods used in conventional analyses. This book is your comprehensive and hands-on guide to understanding various computational statistical simulations using Python. The book begins by helping you get familiarized with the fundamental concepts of simulation modelling, thatll enable you to understand the various methods and techniques needed to explore complex topics. Data scientists working with simulation models will be able to put their knowledge to work with this practical guide. As you advance, youll dive deep into numerical simulation algorithms, including an overview of relevant applications, with the help of real-world use cases and practical examples. Youll also find out how to use Python to develop simulation models and how to use several Python packages. Finally, youll get to grips with various numerical simulation algorithms and concepts, such as Markov Decision Processes, Monte Carlo methods, and bootstrapping techniques.By the end of this book, youll have learned how to construct and deploy simulation models of your own to overcome real-world challenges.What you will learnGet to grips with the concept of randomness and the data generation processDelve into resampling methodsDiscover how to work with Monte Carlo simulationsUtilize simulations to improve or optimize systemsFind out how to run efficient simulations to analyze real-world systemsUnderstand how to simulate random walks using Markov chainsWho this book is forThis book is for data scientists, simulation engineers, and anyone who is already familiar with the basic computational methods and wants to implement various simulation techniques such as Monte-Carlo methods and statistical simulation using Python. Author Biography Giuseppe Ciaburro holds a PhD in environmental technical physics, along with two masters degrees holds a masters degree in chemical engineering from Università degli Studi di Napoli Federico II, and a masters degreeand in acoustic and noise control from Seconda Università degli Studi di Napoli. He works at the Built Environment Control Laboratory - Università degli Studi della Campania "Luigi Vanvitelli".He has over 15 20 years of work experience in programming, first in the field of combustion and then in acoustics and noise control. His core programming knowledge is in Python and R, and he has extensive experience of working with MATLAB. An expert in acoustics and noise control, Giuseppe has wide experience in teaching professional computer ITC courses (about 15 20 years), dealing with e-learning as an author. He has several publications to his credit: monographs, scientific journals, and thematic conferences. He is currently researching machine learning applications in acoustics and noise control. He was recently included in the worlds top 2% scientists list by Stanford University. Table of Contents Table of ContentsIntroducing simulation modelsUnderstanding Randomness and Random NumbersProbability and Data Generating ProcessWorking with Monte Carlo SimulationsSimulation-Based Markov Decision ProcessResampling methodsImproving and optimizing systemsIntroducing evolutionary systemsSimulation models for Financial EngineeringSimulating Physical Phenomena by Neural NetworksModeling and Simulation for Project ManagementSimulation Model for Fault Diagnosis in dynamic systemWhat is next? Details ISBN1804616885 Author Giuseppe Ciaburro Short Title Hands-On Simulation Modeling with Python Language English Year 2022 Edition 2nd ISBN-10 1804616885 ISBN-13 9781804616888 Format Paperback Publisher Packt Publishing Limited Imprint Packt Publishing Limited Place of Publication Birmingham Country of Publication United Kingdom Pages 460 Publication Date 2022-11-30 Subtitle Develop simulation models for improved efficiency and precision in the decision-making process, 2nd Edition AU Release Date 2022-11-30 NZ Release Date 2022-11-30 UK Release Date 2022-11-30 Edition Description 2nd Revised edition DEWEY 003.3 Audience Professional & Vocational We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:139307523;

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