Dive into Python's advanced possibilities, including algorithm analysis, graphs, scale-free networks, and cellular automata with this in-depth, hands-on guide.

Expand your Python skills by working with data structures and algorithms in a refreshing context—through an eye-opening exploration of complexity science. Whether you’re an intermediate-level Python programmer or a student of computational modeling, you’ll delve into examples of complex systems through a series of exercises, case studies, and easy-to-understand explanations. You’ll work with graphs, algorithm analysis, scale-free networks, and cellular automata, using advanced features that make Python such a powerful language. Ideal as a text for courses on Python programming and algorithms, Think Complexity will also help self-learners gain valuable experience with topics and ideas they might not encounter otherwise. Work with NumPy arrays and SciPy methods, basic signal processing and Fast Fourier Transform, and hash tables Study abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machines Get starter code and solutions to help you re-implement and extend original experiments in complexity Explore the philosophy of science, including the nature of scientific laws, theory choice, realism and instrumentalism, and other topics Examine case studies of complex systems submitted by students and readers

The underlying idea and motive for the book is that the notion of complexity may humanize the social sciences, may conceive the complex human being as more human, and turn reality as assumed in our doing social science into a more complex, that is a richer reality for all. The main focus of this book is on new thinking in complexity, with complexity to be taken as derived from the Latin word complexus: ‘that which is interwoven.’ The trans-disciplinary approach advocated here will be trans-disciplinary in two ways: firstly, by going beyond the separate disciplines within the fields of both natural sciences and social sciences, and, secondly, by going beyond the separate cultures of the natural sciences and of the social sciences and humanities.

Since the first edition sold out in less than a year, we now present the revised second edition of Mainzer's popular book. The theory of nonlinear complex systems has become a successful problem-solving approach in the natural sciences from laser physics, quantum chaos, and meteorology to computer simulations of cell growth in biology. It is now recognized that many of our social, ecological, and political problems are also of a global, complex, and nonlinear nature. And one of the most exciting contemporary topics is the idea that even the human mind is governed largely by the nonlinear dynamics of complex systems. In this wide-ranging but concise treatment, Prof. Mainzer discusses, in a nontechnical language, the common framework behind these endeavors. Emphasis is given to the evolution of new structures in natural and cultural systems and we see clearly how the new integrative approach can give insights not available from traditional reductionistic methods.

The book describes what it means to say the world is complex and explores what that means for managers, policy makers and individuals. The first part of the book is about the theory and ideas of complexity. This is explained in a way that is thorough but not mathematical. It compares differing approaches, and also provides a historical perspective, showing how such thinking has been around since the beginning of civilisation. It emphasises the difference between a complexity worldview and the dominant mechanical worldview that underpins much of current management practice. It defines the complexity worldview as recognising the world is interconnected, shaped by history and the particularities of context. The comparison of the differing approaches to modelling complexity is unique in its depth and accessibility. The second part of the book uses this lens of complexity to explore issues in the fields of management, strategy, economics, and international development. It also explores how to facilitate others to recognise the implications of adopting a complex rather than a mechanical worldview and suggests methods of research to explore systemic, path-dependent emergent aspects of situations. The authors of this book span both science and management, academia and practice, thus the explanations of science are authoritative and yet the examples of changing how you live and work in the world are real and accessible. The aim of the book is to bring alive what complexity is all about and to illustrate the importance of loosening the grip of a modernist worldview with its hope for prediction, certainty and control.

Currently used at many colleges, universities, and high schools, this hands-on introduction to computer science is ideal for people with little or no programming experience. The goal of this concise book is not just to teach you Java, but to help you think like a computer scientist. You’ll learn how to program—a useful skill by itself—but you’ll also discover how to use programming as a means to an end. Authors Allen Downey and Chris Mayfield start with the most basic concepts and gradually move into topics that are more complex, such as recursion and object-oriented programming. Each brief chapter covers the material for one week of a college course and includes exercises to help you practice what you’ve learned. Learn one concept at a time: tackle complex topics in a series of small steps with examples Understand how to formulate problems, think creatively about solutions, and write programs clearly and accurately Determine which development techniques work best for you, and practice the important skill of debugging Learn relationships among input and output, decisions and loops, classes and methods, strings and arrays Work on exercises involving word games, graphics, puzzles, and playing cards

The secrets to Apple's success and how to use them, from the Apple insider Ken Segall In Think Simple, Apple insider and New York Times bestselling author Ken Segall gives you the tools to Apple's success - and shows you how to use them. It's all about simplicity. Whether you're in a multinational corporation or a lean startup, this guide will teach you how to crush complexity and focus on what matters; how to perform better, faster and more efficiently. Combining his insight from Apple with examples from companies across industries all over the world - including Ben & Jerry's, Whole Foods, Intel and HyundaiCard - Segall provides a simple roadmap for any company to find success.