# python

## How to Think Like a Computer Scientist: Learning with Python

Allen Downey, Franklin W. Olin College of Engineering

Chris Meyers, Lane Community College

Jeff Elkner, Yorktown High School

*How to Think Like a Computer Scientist: Learning with Python* is an introduction to programming using Python.

(3 reviews)

## Introduction to the Modeling and Analysis of Complex Systems

Hiroki Sayama, State University of New York at Binghamton

*Introduction to the Modeling and Analysis of Complex Systems* introduces students to mathematical/computational modeling and analysis developed in the emerging interdisciplinary field of Complex Systems Science. Complex systems are systems made of a large number of microscopic components interacting with each other in nontrivial ways. Many real-world systems can be understood as complex systems, where critically important information resides in the relationships between the parts and not necessarily within the parts themselves. This textbook offers an accessible yet technically-oriented introduction to the modeling and analysis of complex systems. The topics covered include: fundamentals of modeling, basics of dynamical systems, discrete-time models, continuous-time models, bifurcations, chaos, cellular automata, continuous field models, static networks, dynamic networks, and agent-based models.

(1 review)

## Python for Everybody: Exploring Data Using Python 3

Charles Severance, University of Michigan

I never seemed to find the perfect data-oriented Python book for my course, so I set out to write just such a book. Luckily at a faculty meeting three weeks before I was about to start my new book from scratch over the holiday break, Dr. Atul Prakash showed me the Think Python book which he had used to teach his Python course that semester. It is a well-written Computer Science text with a focus on short, direct explanations and ease of learning. The overall book structure has been changed to get to doing data analysis problems as quickly as possible and have a series of running examples and exercises about data analysis from the very beginning.

(0 reviews)

## Statistical Inference For Everyone

Brian Blais, Bryant University

This is a new approach to an introductory statistical inference textbook, motivated by probability theory as logic.

(0 reviews)

## The Little Book of Semaphores

Allen B. Downey, Franklin W. Olin College of Engineering

*The Little Book of Semaphores* is a free (in both senses of the word) textbook that introduces the principles of synchronization for concurrent programming.

(1 review)

## Think Bayes: Bayesian Statistics Made Simple

Allen B. Downey, Franklin W. Olin College of Engineering

*Think Bayes* is an introduction to Bayesian statistics using computational methods.

(1 review)

## Think Complexity: Exploring Complexity Science with Python

Allen B. Downey, Franklin W. Olin College of Engineering

This book is about complexity science, data structures and algorithms, intermediate programming in Python, and the philosophy of science.

(0 reviews)

## Think DSP: Digital Signal Processing in Python

Allen B. Downey, Franklin W. Olin College of Engineering

*Think DSP* is an introduction to Digital Signal Processing in Python.

(0 reviews)

## Think Python: How to Think Like a Computer Scientist

Allen B. Downey, Franklin W. Olin College of Engineering

*Think Python* is a concise introduction to software design using the Python programming language. Intended for people with no programming experience, this book starts with the most basic concepts and gradually adds new material. Some of the ideas students find most challenging, like recursion and object-oriented programming, are divided into a sequence of smaller steps and introduced over the course of several chapters.

(2 reviews)

## Think Stats: Probability and Statistics for Programmers

Allen B. Downey, Franklin W. Olin College of Engineering

*Think Stats* is an introduction to Probability and Statistics for Python programmers.

(1 review)