Simulation with Python: Develop Simulation and Modeling in Natural Sciences, Engineering, and Social Sciences
- 1h 43m
- Aiichiro Nakano, Rongpeng Li
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.
- 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
About the Author
Ron Li is a long-term and enthusiastic educator. He has been a researcher, data science instructor, and business intelligence engineer. Ron published a highly rated (4.5-star rating out of 5 on amazon) book titled Essential Statistics for Non-STEM Data Analysts. He has also authored/co-authored academic papers, taught (pro bono) data science to non-STEM professionals, and gives talks at conferences such as PyData.
Aiichiro Nakano is a Professor of Computer Science with joint appointments in Physics & Astronomy, Chemical Engineering & Materials Science, Biological Sciences, and at the Collaboratory for Advanced Computing and Simulations at the University of Southern California. He received a PhD in physics from the University of Tokyo, Japan, in 1989. He has authored more than 360 refereed articles in the areas of scalable scientific algorithms, massive data visualization and analysis, and computational materials science.
In this Book
Calculating Pi with Monte Carlo Simulation
Markov Chain, a Peek into the Future
Multi-Armed Bandits, Probability Simulation, and Bayesian Statistics
Balls in a 2-D Box, a Simple Physics Engine
Percolation, Threshold, and Phase Change
Queuing System—How Stock Trades are Made
Rock, Scissors, and Paper—Multi-Agent Simulation
Disease Spreading, Simulating COVID-19 Outbreak
Misinformation Spreading and Simulations on a Graph