Simulation with Python
Develop Simulation and Modeling in Natural Sciences, Engineering, and Social Sciences
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Beschreibung
Understand the theory and implementation of simulation. This book covers simulation topics from a scenario-driven approach using Python and rich visualizations and tabulations.
The book discusses simulation used in the natural and social sciences and with simulations taken from the top algorithms used in the industry today. The authors use an engaging approach that mixes mathematics and programming experiments with beginning-intermediate level Python code to create an immersive learning experience that is cohesive and integrated.
After reading this book, you will have an understanding of simulation used in natural sciences, engineering, and social sciences using Python.
You will:
- Use Python and numerical computation to demonstrate the power of simulation
- Choose a paradigm to run a simulation
- Draw statistical insights from numerical experiments
- Know how simulation is used to solve real-world problems
Understand the theory and implementation of simulation. This book covers simulation topics from a scenario-driven approach using Python and rich visualizations and tabulations.
The book discusses simulation used in the natural and social sciences and with simulations taken from the top algorithms used in the industry today. The authors use an engaging approach that mixes mathematics and programming experiments with beginning-intermediate level Python code to create an immersive learning experience that is cohesive and integrated.
After reading this book, you will have an understanding of simulation used in natural sciences, engineering, and social sciences using Python.
What You'll Learn
- Use Python and numerical computation to demonstrate the power of simulation
- Choose a paradigm to run a simulation
- Draw statistical insights from numerical experiments
- Know how simulation is used to solve real-world problems
Who This Book Is For
Entry-level to mid-level Python developers from various backgrounds, including backend developers, academic research programmers, data scientists, and machine learning engineers. The book is also useful to high school students and college undergraduates and graduates with STEM backgrounds.
Explains mathematics, statistics, network theory, queuing theory, and Monte Carlo simulation, etc. Covers simulation in natural sciences, engineering, and social sciences Includes simulations selected from the top algorithms used in the industry today
Autor*in
Rongpeng Li
Themen in »Simulation with Python«
Numerical Simulation Numerical Calculation Network Theory Computer Simulation Scientific Computation Object Oriented Programming Markov Chain MonteCarlo Simulation