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Hands-On Simulation Modeling with Python
Hands-On Simulation Modeling with Python

Hands-On Simulation Modeling with Python: Develop simulation models to get accurate results and enhance decision-making processes

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Profile Icon Giuseppe Ciaburro
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€18.99 per month
Full star icon Full star icon Full star icon Full star icon Half star icon 4.3 (16 Ratings)
Hardcover Jul 2020 346 pages 1st Edition
eBook
€35.09 €38.99
Hardcover
€48.99
Subscription
Free Trial
Renews at €18.99p/m
Arrow left icon
Profile Icon Giuseppe Ciaburro
Arrow right icon
€18.99 per month
Full star icon Full star icon Full star icon Full star icon Half star icon 4.3 (16 Ratings)
Hardcover Jul 2020 346 pages 1st Edition
eBook
€35.09 €38.99
Hardcover
€48.99
Subscription
Free Trial
Renews at €18.99p/m
eBook
€35.09 €38.99
Hardcover
€48.99
Subscription
Free Trial
Renews at €18.99p/m

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Key benefits

  • Learn to create a digital prototype of a real model using hands-on examples
  • Evaluate the performance and output of your prototype using simulation modeling techniques
  • Understand various statistical and physical simulations to improve systems using Python

Description

Simulation modeling helps you to create digital prototypes of physical models to analyze how they work and predict their performance in the real world. With this comprehensive guide, you'll understand various computational statistical simulations using Python. Starting with the fundamentals of simulation modeling, you'll understand concepts such as randomness and explore data generating processes, resampling methods, and bootstrapping techniques. You'll then cover key algorithms such as Monte Carlo simulations and Markov decision processes, which are used to develop numerical simulation models, and discover how they can be used to solve real-world problems. As you advance, you'll develop simulation models to help you get accurate results and enhance decision-making processes. Using optimization techniques, you'll learn to modify the performance of a model to improve results and make optimal use of resources. The book will guide you in creating a digital prototype using practical use cases for financial engineering, prototyping project management to improve planning, and simulating physical phenomena using neural networks. By the end of this book, you'll have learned how to construct and deploy simulation models of your own to overcome real-world challenges.

Who is this book for?

Hands-On Simulation Modeling with Python is for simulation developers and engineers, model designers, and anyone already familiar with the basic computational methods that are used to study the behavior of systems. This book will help you explore advanced simulation techniques such as Monte Carlo methods, statistical simulations, and much more using Python. Working knowledge of Python programming language is required.

What you will learn

  • Gain an overview of the different types of simulation models
  • Get to grips with the concepts of randomness and data generation process
  • Understand how to work with discrete and continuous distributions
  • Work with Monte Carlo simulations to calculate a definite integral
  • Find out how to simulate random walks using Markov chains
  • Obtain robust estimates of confidence intervals and standard errors of population parameters
  • Discover how to use optimization methods in real-life applications
  • Run efficient simulations to analyze real-world systems

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jul 17, 2020
Length: 346 pages
Edition : 1st
Language : English
ISBN-13 : 9781838985097
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Product Details

Publication date : Jul 17, 2020
Length: 346 pages
Edition : 1st
Language : English
ISBN-13 : 9781838985097
Category :
Languages :

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Table of Contents

15 Chapters
Section 1: Getting Started with Numerical Simulation Chevron down icon Chevron up icon
Chapter 1: Introducing Simulation Models Chevron down icon Chevron up icon
Chapter 2: Understanding Randomness and Random Numbers Chevron down icon Chevron up icon
Chapter 3: Probability and Data Generation Processes Chevron down icon Chevron up icon
Section 2: Simulation Modeling Algorithms and Techniques Chevron down icon Chevron up icon
Chapter 4: Exploring Monte Carlo Simulations Chevron down icon Chevron up icon
Chapter 5: Simulation-Based Markov Decision Processes Chevron down icon Chevron up icon
Chapter 6: Resampling Methods Chevron down icon Chevron up icon
Chapter 7: Using Simulation to Improve and Optimize Systems Chevron down icon Chevron up icon
Section 3: Real-World Applications Chevron down icon Chevron up icon
Chapter 8: Using Simulation Models for Financial Engineering Chevron down icon Chevron up icon
Chapter 9: Simulating Physical Phenomena Using Neural Networks Chevron down icon Chevron up icon
Chapter 10: Modeling and Simulation for Project Management Chevron down icon Chevron up icon
Chapter 11: What's Next? Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

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Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.3
(16 Ratings)
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4 star 25%
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Mahshad Samnejad Dec 23, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Python is increasingly more dominant in the world of programming language, and a book bringing modeling and simulation to the world of python is an absolute necessity.
Amazon Verified review Amazon
TJD Dec 29, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Great book to review simulation models using python!
Amazon Verified review Amazon
Hash Jan 09, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Hands-on Simulation Modeling with Python is all about implementing some of the most famous simulation techniques by Python using standard packages like NumPy, SciPy, Scikit-learn, Pandas, and Matplotlib.Since most of the simulations in the book are based on random processes like Mont Carlo and Brownian motion, the book includes an introduction to mathematical concepts like statistics, probability (e.g., the law of large numbers, central limit theorem, and Markov chain).In addition, some non-statistical approaches like neural networks and numerical optimizations such as Newton-Raphson and gradient descent are discussed in the book.In the latest chapters, modeling of real-world applications such as stock price prediction, risk management, project management, and what-if analysis are taught.This book can be used as a standard coursebook for simulation and modeling or just to learn simulation with python.
Amazon Verified review Amazon
Denis Leach Jan 23, 2025
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The book is well written so far. I have been ill but will now continue.
Feefo Verified review Feefo
Mahshad Samnejad Dec 23, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Python is increasingly more dominant in the world of programming language, and a book bringing modeling and simulation to the world of python is an absolute necessity.
Amazon Verified review Amazon
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