Mathematical Methods Using Python
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Mathematical Methods Using Python
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Author : Vasilis Pagonis
language : en
Publisher: CRC Press
Release Date : 2024-05-14
Mathematical Methods Using Python written by Vasilis Pagonis and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-14 with Computers categories.
This advanced undergraduate textbook presents a new approach to teaching mathematical methods for scientists and engineers. It provides a practical, pedagogical introduction to utilizing Python in Mathematical and Computational Methods courses. Both analytical and computational examples are integrated from its start. Each chapter concludes with a set of problems designed to help students hone their skills in mathematical techniques, computer programming, and numerical analysis. The book places less emphasis on mathematical proofs, and more emphasis on how to use computers for both symbolic and numerical calculations. It contains 182 extensively documented coding examples, based on topics that students will encounter in their advanced courses in Mechanics, Electronics, Optics, Electromagnetism, Quantum Mechanics etc. An introductory chapter gives students a crash course in Python programming and the most often used libraries (SymPy, NumPy, SciPy, Matplotlib). This is followed by chapters dedicated to differentiation, integration, vectors and multiple integration techniques. The next group of chapters covers complex numbers, matrices, vector analysis and vector spaces. Extensive chapters cover ordinary and partial differential equations, followed by chapters on nonlinear systems and on the analysis of experimental data using linear and nonlinear regression techniques, Fourier transforms, binomial and Gaussian distributions. The book is accompanied by a dedicated GitHub website, which contains all codes from the book in the form of ready to run Jupyter notebooks. A detailed solutions manual is also available for instructors using the textbook in their courses. Key Features: A unique teaching approach which merges mathematical methods and the Python programming skills which physicists and engineering students need in their courses Uses examples and models from physical and engineering systems, to motivate the mathematics being taught Students learn to solve scientific problems in three different ways: traditional pen-and-paper methods, using scientific numerical techniques with NumPy and SciPy, and using Symbolic Python (SymPy).
Mathematical Physics Using Python
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Author : Vasilis Pagonis
language : en
Publisher:
Release Date : 2024
Mathematical Physics Using Python written by Vasilis Pagonis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with Science categories.
"This advanced undergraduate textbook provides a practical, pedagogical lead introduction to utilizing Python for Mathematical Physics and Computational Physics courses. Both analytical and computational example problems are integrated from its start, in addition to featuring end of chapter problems, designed to help students hone their skills in mathematical physics techniques, computer programming, and in numerical analysis. It places much less emphasis on mathematical proofs, and more emphasis on how to use computers for both numerical and symbolic calculations. This book will, therefore, provide both students and instructors with a clear presentation of the typical topics covered in a Mathematical Physics course and will present an accessible and practical instruction on how to use computational techniques to solve physics problems, by using the Python programming language. Students using the textbook will solve physics problems in three different ways: (a) Using the traditional pen-and-paper methods (b) Using scientific numerical techniques with the Python packages NumPy and SciPy (c) Using the Symbolic Python packages (e.g. SymPy). The book is accompanied by a dedicated GitHub website, which will contain all sample code used in the examples. In the same website, links will be provided for the many available resources online that a student can use in order to learn about specific Python topics. A solutions manual is also available for instructors using the textbook in their course"--
Computational Physics
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Author : Rubin H. Landau
language : en
Publisher: John Wiley & Sons
Release Date : 2024-03-25
Computational Physics written by Rubin H. Landau and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-25 with Science categories.
The classic in the field for more than 25 years, now with increased emphasis on data science and new chapters on quantum computing, machine learning (AI), and general relativity Computational physics combines physics, applied mathematics, and computer science in a cutting-edge multidisciplinary approach to solving realistic physical problems. It has become integral to modern physics research because of its capacity to bridge the gap between mathematical theory and real-world system behavior. Computational Physics provides the reader with the essential knowledge to understand computational tools and mathematical methods well enough to be successful. Its philosophy is rooted in “learning by doing”, assisted by many sample programs in the popular Python programming language. The first third of the book lays the fundamentals of scientific computing, including programming basics, stable algorithms for differentiation and integration, and matrix computing. The latter two-thirds of the textbook cover more advanced topics such linear and nonlinear differential equations, chaos and fractals, Fourier analysis, nonlinear dynamics, and finite difference and finite elements methods. A particular focus in on the applications of these methods for solving realistic physical problems. Readers of the fourth edition of Computational Physics will also find: An exceptionally broad range of topics, from simple matrix manipulations to intricate computations in nonlinear dynamics A whole suite of supplementary material: Python programs, Jupyter notebooks and videos Computational Physics is ideal for students in physics, engineering, materials science, and any subjects drawing on applied physics.
Programming For Computations Python
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Author : Svein Linge
language : en
Publisher: Springer
Release Date : 2016-07-25
Programming For Computations Python written by Svein Linge and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-25 with Computers categories.
This book presents computer programming as a key method for solving mathematical problems. There are two versions of the book, one for MATLAB and one for Python. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows the students to write simple programs for solving common mathematical problems with numerical methods in engineering and science courses. The emphasis is on generic algorithms, clean design of programs, use of functions, and automatic tests for verification.
Mathematical Methods In Data Science
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Author : Sébastien Roch
language : en
Publisher: Cambridge University Press
Release Date : 2025-09-30
Mathematical Methods In Data Science written by Sébastien Roch and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-30 with Computers categories.
Bridge the gap between theoretical concepts and their practical applications with this rigorous introduction to the mathematics underpinning data science. It covers essential topics in linear algebra, calculus and optimization, and probability and statistics, demonstrating their relevance in the context of data analysis. Key application topics include clustering, regression, classification, dimensionality reduction, network analysis, and neural networks. What sets this text apart is its focus on hands-on learning. Each chapter combines mathematical insights with practical examples, using Python to implement algorithms and solve problems. Self-assessment quizzes, warm-up exercises and theoretical problems foster both mathematical understanding and computational skills. Designed for advanced undergraduate students and beginning graduate students, this textbook serves as both an invitation to data science for mathematics majors and as a deeper excursion into mathematics for data science students.
Numerical Methods In Physics With Python
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Author : Alex Gezerlis
language : en
Publisher: Cambridge University Press
Release Date : 2023-07-20
Numerical Methods In Physics With Python written by Alex Gezerlis and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-20 with Science categories.
Bringing together idiomatic Python programming, foundational numerical methods, and physics applications, this is an ideal standalone textbook for courses on computational physics. All the frequently used numerical methods in physics are explained, including foundational techniques and hidden gems on topics such as linear algebra, differential equations, root-finding, interpolation, and integration. The second edition of this introductory book features several new codes and 140 new problems (many on physics applications), as well as new sections on the singular-value decomposition, derivative-free optimization, Bayesian linear regression, neural networks, and partial differential equations. The last section in each chapter is an in-depth project, tackling physics problems that cannot be solved without the use of a computer. Written primarily for students studying computational physics, this textbook brings the non-specialist quickly up to speed with Python before looking in detail at the numerical methods often used in the subject.
Mathematical Methods For Knowledge Discovery And Data Mining
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Author : Giovanni Felici
language : en
Publisher: IGI Global Snippet
Release Date : 2008
Mathematical Methods For Knowledge Discovery And Data Mining written by Giovanni Felici and has been published by IGI Global Snippet this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Business & Economics categories.
Annotation The field of data mining has seen a demand in recent years for the development of ideas and results in an integrated structure. Mathematical Methods for Knowledge Discovery & Data Mining focuses on the mathematical models and methods that support most data mining applications and solution techniques, covering such topics as association rules; Bayesian methods; data visualization; kernel methods; neural networks; text, speech, and image recognition; and many others. This Premier Reference Source is an invaluable resource for scholars and practitioners in the fields of biomedicine, engineering, finance and insurance, manufacturing, marketing, performance measurement, and telecommunications.
Programming For Computations Python
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Author : Svein Linge
language : en
Publisher: Springer Nature
Release Date : 2019-10-30
Programming For Computations Python written by Svein Linge and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-30 with Computers categories.
This book is published open access under a CC BY 4.0 license. This book presents computer programming as a key method for solving mathematical problems. This second edition of the well-received book has been extensively revised: All code is now written in Python version 3.6 (no longer version 2.7). In addition, the two first chapters of the previous edition have been extended and split up into five new chapters, thus expanding the introduction to programming from 50 to 150 pages. Throughout the book, the explanations provided are now more detailed, previous examples have been modified, and new sections, examples and exercises have been added. Also, a number of small errors have been corrected. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style employed is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows students to write simple programs for solving common mathematical problems with numerical methods in the context of engineering and science courses. The emphasis is on generic algorithms, clean program design, the use of functions, and automatic tests for verification.
Applied Scientific Computing
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Author : Peter R. Turner
language : en
Publisher: Springer
Release Date : 2018-07-18
Applied Scientific Computing written by Peter R. Turner and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-18 with Computers categories.
This easy-to-understand textbook presents a modern approach to learning numerical methods (or scientific computing), with a unique focus on the modeling and applications of the mathematical content. Emphasis is placed on the need for, and methods of, scientific computing for a range of different types of problems, supplying the evidence and justification to motivate the reader. Practical guidance on coding the methods is also provided, through simple-to-follow examples using Python. Topics and features: provides an accessible and applications-oriented approach, supported by working Python code for many of the methods; encourages both problem- and project-based learning through extensive examples, exercises, and projects drawn from practical applications; introduces the main concepts in modeling, python programming, number representation, and errors; explains the essential details of numerical calculus, linear, and nonlinear equations, including the multivariable Newton method; discusses interpolation and the numerical solution of differential equations, covering polynomial interpolation, splines, and the Euler, Runge–Kutta, and shooting methods; presents largely self-contained chapters, arranged in a logical order suitable for an introductory course on scientific computing. Undergraduate students embarking on a first course on numerical methods or scientific computing will find this textbook to be an invaluable guide to the field, and to the application of these methods across such varied disciplines as computer science, engineering, mathematics, economics, the physical sciences, and social science.
The Statistics And Calculus With Python Workshop
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Author : Peter Farrell
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-08-18
The Statistics And Calculus With Python Workshop written by Peter Farrell and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-18 with Computers categories.
With examples and activities that help you achieve real results, applying calculus and statistical methods relevant to advanced data science has never been so easy Key FeaturesDiscover how most programmers use the main Python libraries when performing statistics with PythonUse descriptive statistics and visualizations to answer business and scientific questionsSolve complicated calculus problems, such as arc length and solids of revolution using derivatives and integralsBook Description Are you looking to start developing artificial intelligence applications? Do you need a refresher on key mathematical concepts? Full of engaging practical exercises, The Statistics and Calculus with Python Workshop will show you how to apply your understanding of advanced mathematics in the context of Python. The book begins by giving you a high-level overview of the libraries you'll use while performing statistics with Python. As you progress, you'll perform various mathematical tasks using the Python programming language, such as solving algebraic functions with Python starting with basic functions, and then working through transformations and solving equations. Later chapters in the book will cover statistics and calculus concepts and how to use them to solve problems and gain useful insights. Finally, you'll study differential equations with an emphasis on numerical methods and learn about algorithms that directly calculate values of functions. By the end of this book, you'll have learned how to apply essential statistics and calculus concepts to develop robust Python applications that solve business challenges. What you will learnGet to grips with the fundamental mathematical functions in PythonPerform calculations on tabular datasets using pandasUnderstand the differences between polynomials, rational functions, exponential functions, and trigonometric functionsUse algebra techniques for solving systems of equationsSolve real-world problems with probabilitySolve optimization problems with derivatives and integralsWho this book is for If you are a Python programmer who wants to develop intelligent solutions that solve challenging business problems, then this book is for you. To better grasp the concepts explained in this book, you must have a thorough understanding of advanced mathematical concepts, such as Markov chains, Euler's formula, and Runge-Kutta methods as the book only explains how these techniques and concepts can be implemented in Python.