Hands-On Simulation Modeling with Python: Develop simulation models for improved efficiency and precision in the decision-making process, Edition 2
About this ebook
- Understand various statistical and physical simulations to improve systems using Python
- Learn to create the numerical prototype of a real model using hands-on examples
- Evaluate performance and output results based on how the prototype would work in the real world
- Get to grips with the concept of randomness and the data generation process
- Delve into resampling methods
- Discover how to work with Monte Carlo simulations
- Utilize simulations to improve or optimize systems
- Find out how to run efficient simulations to analyze real-world systems
- Understand how to simulate random walks using Markov chains
This 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.
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About the author
Giuseppe Ciaburro holds a PhD and two master's degrees. He works at the Built Environment Control Laboratory - Università degli Studi della Campania "Luigi Vanvitelli". He has over 25 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 MATLAB, Python and R. As an expert in AI applications to acoustics and noise control problems, Giuseppe has wide experience in researching and teaching. He has several publications to his credit: monographs, scientific journals, and thematic conferences. He was recently included in the world's top 2% scientists list by Stanford University (2022).
