Welcome to Ian Stewart's strange and magical world of mathematics! In Math Hysteria, Professor Stewart presents us with a wealth of magical puzzles, each one spun around an amazing tale: Counting the Cattle of the Sun; The Great Drain Robbery; and Preposterous Piratical Predicaments; to name but a few. Along the way, we also meet many curious characters: in short, these stori...(展开全部)

肯·宾默尔是一个从数学转行的经济学家，他把一生贡献给了博弈论及其在经济学、进化生物学、心理学和道德哲学中的应用。他因为参与设计为英国纳税人赚了350亿美元的电信拍卖而闻名于世，但其主要研究贡献在于议价理论及其实验检验。他是英国科学院和美国艺术与科学研究院的院士。他著有12本著作和大约90篇研究论文。他是伦敦大学学院的经济学名誉教授。

This text provides a historical, scientific, and cultural framework for the basic elements of mathematics characteristic of a typical college curriculum. Designed for students with a solid background in high school mathematics, it features nine chapters that range from number theory to applications. 1983 edition.

Python, one of the world's most popular programming languages, has a number of powerful packages to help you tackle complex mathematical problems in a simple and efficient way. These core capabilities help programmers pave the way for building exciting applications in various domains, such as machine learning and data science, using knowledge in the computational mathematics domain.The book teaches you how to solve problems faced in a wide variety of mathematical fields, including calculus, probability, statistics and data science, graph theory, optimization, and geometry. You'll start by developing core skills and learning about packages covered in Python’s scientific stack, including NumPy, SciPy, and Matplotlib. As you advance, you'll get to grips with more advanced topics of calculus, probability, and networks (graph theory). After you gain a solid understanding of these topics, you'll discover Python's applications in data science and statistics, forecasting, geometry, and optimization. The final chapters will take you through a collection of miscellaneous problems, including working with specific data formats and accelerating code.By the end of this book, you'll have an arsenal of practical coding solutions that can be used and modified to solve a wide range of practical problems in computational mathematics and data science.

罗伯特•费希尔（Robert Fisher）：布鲁内尔大学的教育学教授。他曾在英国、非洲和香港等地从事教育工作20余年。此外，他还著有30余本教育学方面的专著，包括《教孩子学会思考》（Teaching Children to Think）、《教孩子学会学习》（Teaching Children to Learn）、《思考的故事》（Stories for Thinking）和《创造性对话》（Creative Dialogue）等。 更多关于孩子教育的信息，请参阅罗伯特•费希尔教授的网页：www.teachingthinking.net

Fascinating study considers the origins and nature of mathematics, its development and role in the history of scientific thinking, impact of high-speed computers, 20th-century changes in the foundations of mathematics and mathematical logic, mathematization of science and technology, much more. Compelling reading for anyone interested in the evolution of mathematical thought. I...(展开全部)