Introduction to Programming Concepts with Case Studies in Python, G?kt?rk ??oluk; Sinan Kalkan
Автор: Langtangen Hans Petter Название: A Primer on Scientific Programming with Python ISBN: 3662498863 ISBN-13(EAN): 9783662498866 Издательство: Springer Рейтинг: Цена: 4890.00 р. 6986.00-30% Наличие на складе: Есть (1 шт.) 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
Автор: Lewis Название: Introduction to the Art of Programming Using Scala ISBN: 1439896666 ISBN-13(EAN): 9781439896662 Издательство: Taylor&Francis Рейтинг: Цена: 12707.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: With its flexibility for programming both small and large projects, Scala is an ideal language for teaching beginning programming. Yet there are no textbooks on Scala currently available for the CS1/CS2 levels. Introduction to the Art of Programming Using Scala presents many concepts from CS1 and CS2 using a modern, JVM-based language that works well for both programming in the small and programming in the large. The book progresses from true programming in the small to more significant projects later, leveraging the full benefits of object orientation. It first focuses on fundamental problem solving and programming in the small using the REPL and scripting environments. It covers basic logic and problem decomposition and explains how to use GUIs and graphics in programs. The text then illustrates the benefits of object-oriented design and presents a large collection of basic data structures showing different implementations of key ADTs along with more atypical data structures. It also introduces multithreading and networking to provide further motivating examples. By using Scala as the language for both CS1 and CS2 topics, this textbook gives students an easy entry into programming small projects as well as a firm foundation for taking on larger-scale projects. Many student and instructor resources are available at www.programmingusingscala.net
Makes Numerical Programming More Accessible to a Wider Audience
Bearing in mind the evolution of modern programming, most specifically emergent programming languages that reflect modern practice, Numerical Programming: A Practical Guide for Scientists and Engineers Using Python and C/C++ utilizes the author's many years of practical research and teaching experience to offer a systematic approach to relevant programming concepts. Adopting a practical, broad appeal, this user-friendly book offers guidance to anyone interested in using numerical programming to solve science and engineering problems.Emphasizing methods generally used in physics and engineering--from elementary methods to complex algorithms--it gradually incorporates algorithmic elements with increasing complexity.
Develop a Combination of Theoretical Knowledge, Efficient Analysis Skills, and Code Design Know-How
The book encourages algorithmic thinking, which is essential to numerical analysis. Establishing the fundamental numerical methods, application numerical behavior and graphical output needed to foster algorithmic reasoning, coding dexterity, and a scientific programming style, it enables readers to successfully navigate relevant algorithms, understand coding design, and develop efficient programming skills. The book incorporates real code, and includes examples and problem sets to assist in hands-on learning.
Begins with an overview on approximate numbers and programming in Python and C/C++, followed by discussion of basic sorting and indexing methods, as well as portable graphic functionality
Contains methods for function evaluation, solving algebraic and transcendental equations, systems of linear algebraic equations, ordinary differential equations, and eigenvalue problems
Addresses approximation of tabulated functions, regression, integration of one- and multi-dimensional functions by classical and Gaussian quadratures, Monte Carlo integration techniques, generation of random variables, discretization methods for ordinary and partial differential equations, and stability analysis
This text introduces platform-independent numerical programming using Python and C/C++, and appeals to advanced undergraduate and graduate students in natural sciences and engineering, researchers involved in scientific computing, and engineers carrying out applicative calculations.
Описание: Combining GIS concepts and fundamental spatial thinking methodology with real programming examples, this book introduces popular Python-based tools and their application to solving real-world problems. It elucidates the programming constructs of Python with its high-level toolkits and demonstrates its integration with ArcGIS Theory. Filled with hands-on computer exercises in a logical learning workflow this book promotes increased interactivity between instructors and students while also benefiting professionals in the field with vital knowledge to sharpen their programming skills. Readers receive expert guidance on modules, package management, and handling shapefile formats needed to build their own mini-GIS. Comprehensive and engaging commentary, robust contents, accompanying datasets, and classroom-tested exercises are all housed here to permit users to become competitive in the GIS/IT job market and industry.
Автор: Yue Zhang Название: An Introduction to Python and Computer Programming ISBN: 9812876081 ISBN-13(EAN): 9789812876089 Издательство: Springer Рейтинг: Цена: 19591.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces Python programming language and fundamental concepts in algorithms and computing.
Автор: Yue Zhang Название: An Introduction to Python and Computer Programming ISBN: 9811012431 ISBN-13(EAN): 9789811012433 Издательство: Springer Рейтинг: Цена: 16977.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces Python programming language and fundamental concepts in algorithms and computing.
A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.
Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context.
After discussing the trajectory from data to insight to decision, the book describes four approaches to machine learning: information-based learning, similarity-based learning, probability-based learning, and error-based learning. Each of these approaches is introduced by a nontechnical explanation of the underlying concept, followed by mathematical models and algorithms illustrated by detailed worked examples. Finally, the book considers techniques for evaluating prediction models and offers two case studies that describe specific data analytics projects through each phase of development, from formulating the business problem to implementation of the analytics solution. The book, informed by the authors' many years of teaching machine learning, and working on predictive data analytics projects, is suitable for use by undergraduates in computer science, engineering, mathematics, or statistics; by graduate students in disciplines with applications for predictive data analytics; and as a reference for professionals.
Описание: Addressing students, mechanical engineers, technicians and experienced automation engineers, the book will assist to understand and to use OOP in accordance with IEC 61131-3. In a step-by-step process, example programs show how to design a ready-to-use machine module.
Автор: Dory Michael, Parrish Allison, Berg Brendan Название: Introduction to Tornado: Modern Web Applications with Python ISBN: 1449309070 ISBN-13(EAN): 9781449309077 Издательство: Wiley Рейтинг: Цена: 3008.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Tornado is a scalable, non-blocking web server and web application framework written in Python. It is also light-weight to deploy, fun to write for, and incredibly powerful. Tornado was written with performance in mind, aiming to solve the C10k problem, so by design it`s an extremely high-performance framework.
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