Allen Downey is a Staff Scientist at DrivenData and Professor Emeritus at Olin College, where he taught Modeling and Simulation and other classes related to software and data science. He is the author of several textbooks, including Think Python, Think Bayes, and Elements of Data Science. Previously, he taught at Wellesley College and Colby College. He received his Ph.D. in computer science from the University of California, Berkeley in 1997. His undergraduate and master's degrees are from the Civil Engineering department at MIT. He is the author of Probably Overthinking It, a blog about data science and Bayesian statistics.
Modeling and Simulation in Python is an introduction to physical modeling using a computational approach . . . Taking a computational approach makes it possible to work with more realistic models than what you typically see in a first-year physics class, with the option to include features like friction and drag. -Python Kitchen Allen Downey's Modeling and Simulation in Python provides a wealth of instructive examples of all kinds of modeling. . . . this book can be valuable as a textbook for classes on scientific computation, or as a guide to exploration for interested amateurs. -Bradford Tuckfield, Author of Dive into Algorithms and Dive Into Data Science This book is designed for newcomers to both Python and computer modeling. If you've read Think Python, you know that Downey is an accomplished teacher, and here he uses a combination of Python, calculus, bespoke helper functions, and easily-accessible online materials to model a diverse and interesting set of simulation projects. In the process, he presents a practical and reusable framework for modeling dynamical systems with Python. -Lee Vaughan, Author of Python Tools for Scientists, Real-World Python, and Impractical Python Projects, and former Senior Principal Scientist for Geological Modeling at ExxonMobil Allen Downey's Modeling and Simulation in Python provides an impressive introduction to physical modeling and Python programming, featuring clear, concise explanations and examples. Covering a wide range of topics, from world population growth to celestial mechanics, it provides a comprehensive look at the tools and processes of computational simulation, perfect for readers of any level. . . . With a wide variety of practical and fun example projects, readers get all they need to master the art of modeling and simulation in Python. -Christian Mayer, Bestselling Author (Python One-Liners) and Founder of the Coding Academy Finxter.com