Автор: Langtangen Hans Petter Название: A Primer on Scientific Programming with Python ISBN: 3662498863 ISBN-13(EAN): 9783662498866 Издательство: Springer Рейтинг: Цена: 32600.00 T Наличие на складе: Есть Описание: The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches 'Matlab-style' and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science.From the reviews: Langtangen … does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. … Summing Up: Highly recommended. F. H. Wild III, Choice, Vol. 47 (8), April 2010Those of us who have learned scientific programming in Python ‘on the streets’ could be a little jealous of students who have the opportunity to take a course out of Langtangen’s Primer.” John D. Cook, The Mathematical Association of America, September 2011This book goes through Python in particular, and programming in general, via tasks that scientists will likely perform. It contains valuable information for students new to scientific computing and would be the perfect bridge between an introduction to programming and an advanced course on numerical methods or computational science.Alex Small, IEEE, CiSE Vol. 14 (2), March?/April 2012 “This fourth edition is awonderful, inclusive textbook that covers pretty much everything one needs toknow to go from zero to fairly sophisticated scientific programming in Python…”Joan Horvath, Computing Reviews, March2015
The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization.
This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (MOOC). This new edition has been updated for Python 3, reorganized to make it easier to use for courses that cover only a subset of the material, and offers additional material including five new chapters.
Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming. This edition offers expanded material on statistics and machine learning and new chapters on Frequentist and Bayesian statistics.
Автор: Bernard Название: Python Recipes Handbook ISBN: 1484202422 ISBN-13(EAN): 9781484202425 Издательство: Springer Рейтинг: Цена: 23280.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Learn the code to write algorithms, numerical computations, data analysis and much more using the Python language: look up and re-use the recipes for your own Python coding. This book is your handy code cookbook reference. Whether you're a maker, game developer, cloud computing programmer and more, this is a must-have reference for your library. Python Recipes Handbook gives you the most common and contemporary code snippets, using pandas (Python Data Analysis Library), NumPy, and other numerical Python packages. What You'll LearnCode with the pandas (Python Data Analysis Library)Work with the various Python algorithms useful for today's big data analytics and cloud applicationsUse NumPy and other numerical Python packages and code for doing various kinds of analysisDiscover Python's new popular modules, packages, extensions and templates libraryWho This Book Is ForThis handy reference is for those with some experience with Python.
Автор: Gerrard Название: Lean Python ISBN: 1484223845 ISBN-13(EAN): 9781484223840 Издательство: Springer Рейтинг: Цена: 21420.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Learn only the essential aspects of Python without cluttering up your mind with features you may never use. This compact book is not a 'best way to write code' type of book; rather, the author goes over his most-used functions, which are all you need to know as a beginner and some way beyond.Lean Python takes 58 Python methods and functions and whittles them down to 15: as author Paul Gerrard says, 'I haven't found a need for the rest.'
What You'll Learn
Discover lean Python and how to learn just enough to build useful toolsUse Python objects, program structure, I/O, modules and moreHandle errors and exceptions Test your codeAccess the Web; do searching; and persist data
Who This Book Is For
This book is aimed at three categories of reader: The experienced programmer – if you already know a programming language, this book gives you a shortcut to understanding the Python language and some of its design philosophy.
You work in IT and need a programming primer – you might be a tester who needs to have more informed technical discussions with programmers. Working through the examples will help you to appreciate the challenge of good programming.
First-timer – you want a first book on programming that you can assimilate quickly to help you decide whether programming is for you.
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