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| Author | : Michael Harry Beilby |
| Publisher | : |
| Total Pages | : 438 |
| Release | : 1991 |
| Genre | : Computer programming |
| ISBN | : 9780750301282 |
| Author | : M. H. Beilby |
| Publisher | : CRC Press |
| Total Pages | : 438 |
| Release | : 2003-02-01 |
| Genre | : Computer programming |
| ISBN | : 9780750301299 |
| Author | : M.H Beilby |
| Publisher | : CRC Press |
| Total Pages | : 447 |
| Release | : 2022-02-15 |
| Genre | : Computers |
| ISBN | : 1000111377 |
The Scientific Programmer's Toolkit: Turbo Pascal Edition presents a complete software environment for anyone writing programs in mathematical, engineering, or science areas. This toolkit package is designed for use with Turbo Pascal, the de facto standard Pascal system for PC and compatible machines. The book and its software provides an integrated software library of programming tools. The programs and routines fall into three categories: graphical, mathematical, and utilities. Routines are further subdivided into three levels that reflect the experience of the user. For graphics and text handling routines there is also a Level 0, which provides an interface to the machine operating system. By using hierarchically structured routines, the clearly written text, and a wide range of example programs, software users can construct a user-friendly interface with minimal effort. The levels structure makes it easy for newcomers to use the Toolkit, and with growing experience, users can achieve more elaborate effects. The Scientific Programmer's Toolkit will be useful to consultants, researchers, and students in any quantitative profession or science, in private or public sector research establishments, or in secondary and higher education.
| Author | : Joakim Sundnes |
| Publisher | : |
| Total Pages | : 157 |
| Release | : 2020 |
| Genre | : Computer programming |
| ISBN | : 3030503569 |
This open access book offers an initial introduction to programming for scientific and computational applications using the Python programming language. The presentation style is compact and example-based, making it suitable for students and researchers with little or no prior experience in programming. The book uses relevant examples from mathematics and the natural sciences to present programming as a practical toolbox that can quickly enable readers to write their own programs for data processing and mathematical modeling. These tools include file reading, plotting, simple text analysis, and using NumPy for numerical computations, which are fundamental building blocks of all programs in data science and computational science. At the same time, readers are introduced to the fundamental concepts of programming, including variables, functions, loops, classes, and object-oriented programming. Accordingly, the book provides a sound basis for further computer science and programming studies.
| Author | : Hans Petter Langtangen |
| Publisher | : Springer |
| Total Pages | : 942 |
| Release | : 2016-07-28 |
| Genre | : Computers |
| ISBN | : 3662498871 |
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 2010 Those 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 2011 This 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 a wonderful, inclusive textbook that covers pretty much everything one needs to know to go from zero to fairly sophisticated scientific programming in Python...” Joan Horvath, Computing Reviews, March 2015
| Author | : James T. Smith |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 399 |
| Release | : 2013-03-09 |
| Genre | : Computers |
| ISBN | : 1461214742 |
This concise guide covers the fundamental aspects of the numerical analysis, basing upon it the construction of its routines for solving nonlinear equations, linear and nonlinear systems of equations, and eigenvalue problems. Focusing on software development, this book emphasizes software tools, OOP techniques for handling vectors, polynomials, and matrices. Using actual examples to demonstrate reusable tools, the book enables readers to solve broad classes of software development and programming challenges. It adopts a balanced approach between OOP techniques and quick and dirty number crunching, and emphasizes the use of OOP features in implementing vector, polynomial and matrix algebra. As a practical reference, it will help developers and consultants setting up applications programs for electrical, electronic engineering and physical sciences who need to develop clean, efficient C++ programs in minimal time.
| Author | : Jake VanderPlas |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 743 |
| Release | : 2016-11-21 |
| Genre | : Computers |
| ISBN | : 1491912138 |
For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms
| Author | : Greg Reid |
| Publisher | : Hodder Gibson |
| Total Pages | : 131 |
| Release | : 2015-09-25 |
| Genre | : Computers |
| ISBN | : 1471836053 |
Exam Board: SQA Level: Higher Subject: Computing Science First Teaching: September 2014 First Exam: Summer 2015 Get your best grade with the SQA endorsed guide to Higher Computing Science for CfE. This book contains all the advice and support you need to revise successfully for your Higher (for CfE) exam. It combines an overview of the course syllabus with advice from a top expert on how to improve exam performance, so you have the best chance of success. · Refresh your knowledge with complete course notes · Prepare for the exam with top tips and hints on revision techniques · Get your best grade with advice on how to gain those vital extra marks
| Author | : John Paul Mueller |
| Publisher | : John Wiley & Sons |
| Total Pages | : 768 |
| Release | : 2020-01-09 |
| Genre | : Computers |
| ISBN | : 1119626110 |
Your logical, linear guide to the fundamentals of data science programming Data science is exploding—in a good way—with a forecast of 1.7 megabytes of new information created every second for each human being on the planet by 2020 and 11.5 million job openings by 2026. It clearly pays dividends to be in the know. This friendly guide charts a path through the fundamentals of data science and then delves into the actual work: linear regression, logical regression, machine learning, neural networks, recommender engines, and cross-validation of models. Data Science Programming All-In-One For Dummies is a compilation of the key data science, machine learning, and deep learning programming languages: Python and R. It helps you decide which programming languages are best for specific data science needs. It also gives you the guidelines to build your own projects to solve problems in real time. Get grounded: the ideal start for new data professionals What lies ahead: learn about specific areas that data is transforming Be meaningful: find out how to tell your data story See clearly: pick up the art of visualization Whether you’re a beginning student or already mid-career, get your copy now and add even more meaning to your life—and everyone else’s!
| Author | : Peter Sloot |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 1188 |
| Release | : 2003-05-22 |
| Genre | : Computers |
| ISBN | : 3540401970 |
The four-volume set LNCS 2657, LNCS 2658, LNCS 2659, and LNCS 2660 constitutes the refereed proceedings of the Third International Conference on Computational Science, ICCS 2003, held concurrently in Melbourne, Australia and in St. Petersburg, Russia in June 2003. The four volumes present more than 460 reviewed contributed and invited papers and span the whole range of computational science, from foundational issues in computer science and algorithmic mathematics to advanced applications in virtually all application fields making use of computational techniques. These proceedings give a unique account of recent results in the field.
