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| from math import sin: Python Scripting for Computational Science Hans Petter Langtangen, 2013-03-14 Scripting with Python makes you productive and increases the reliability of your scientific work. Here, the author teaches you how to develop tailored, flexible, and efficient working environments built from small programs (scripts) written in Python. The focus is on examples and applications of relevance to computational science: gluing existing applications and tools, e.g. for automating simulation, data analysis, and visualization; steering simulations and computational experiments; equipping programs with graphical user interfaces; making computational Web services; creating interactive interfaces with a Maple/Matlab-like syntax to numerical applications in C/C++ or Fortran; and building flexible object-oriented programming interfaces to existing C/C++ or Fortran libraries. |
| from math import sin: A Primer on Scientific Programming with Python Hans Petter Langtangen, 2016-07-28 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 |
| from math import sin: A Functional Start to Computing with Python Ted Herman, 2013-07-26 A Functional Start to Computing with Python enables students to quickly learn computing without having to use loops, variables, and object abstractions at the start. Requiring no prior programming experience, the book draws on Python’s flexible data types and operations as well as its capacity for defining new functions. Along with the specifics of Python, the text covers important concepts of computing, including software engineering motivation, algorithms behind syntax rules, advanced functional programming ideas, and, briefly, finite state machines. Taking a student-friendly, interactive approach to teach computing, the book addresses more difficult concepts and abstractions later in the text. The author presents ample explanations of data types, operators, and expressions. He also describes comprehensions—the powerful specifications of lists and dictionaries—before introducing loops and variables. This approach helps students better understand assignment syntax and iteration by giving them a mental model of sophisticated data first. Web Resource The book’s supplementary website at http://functionalfirstpython.com/ provides many ancillaries, including: Interactive flashcards on Python language elements Links to extra support for each chapter Unit testing and programming exercises An interactive Python stepper tool Chapter-by-chapter points Material for lectures |
| from math import sin: Linux Commands, C, C++, Java and Python Exercises For Beginners Manjunath.R, 2020-03-27 Hands-On Practice for Learning Linux and Programming Languages from Scratch Are you new to Linux and programming? Do you want to learn Linux commands and programming languages like C, C++, Java, and Python but don't know where to start? Look no further! An approachable manual for new and experienced programmers that introduces the programming languages C, C++, Java, and Python. This book is for all programmers, whether you are a novice or an experienced pro. It is designed for an introductory course that provides beginning engineering and computer science students with a solid foundation in the fundamental concepts of computer programming. In this comprehensive guide, you will learn the essential Linux commands that every beginner should know, as well as gain practical experience with programming exercises in C, C++, Java, and Python. It also offers valuable perspectives on important computing concepts through the development of programming and problem-solving skills using the languages C, C++, Java, and Python. The beginner will find its carefully paced exercises especially helpful. Of course, those who are already familiar with programming are likely to derive more benefits from this book. After reading this book you will find yourself at a moderate level of expertise in C, C++, Java and Python, from which you can take yourself to the next levels. The command-line interface is one of the nearly all well built trademarks of Linux. There exists an ocean of Linux commands, permitting you to do nearly everything you can be under the impression of doing on your Linux operating system. However, this, at the end of time, creates a problem: because of all of so copious commands accessible to manage, you don't comprehend where and at which point to fly and learn them, especially when you are a learner. If you are facing this problem, and are peering for a painless method to begin your command line journey in Linux, you've come to the right place-as in this book, we will launch you to a hold of well liked and helpful Linux commands. This book gives a thorough introduction to the C, C++, Java, and Python programming languages, covering everything from fundamentals to advanced concepts. It also includes various exercises that let you put what you learn to use in the real world. With step-by-step instructions and plenty of examples, you'll build your knowledge and confidence in Linux and programming as you progress through the exercises. By the end of the book, you'll have a solid foundation in Linux commands and programming concepts, allowing you to take your skills to the next level. Whether you're a student, aspiring programmer, or curious hobbyist, this book is the perfect resource to start your journey into the exciting world of Linux and programming! |
| from math import sin: The Art of Go - Basics Harry Yoon, 2021-05-05 Learn Golang Programming by Reading This Book! Go is one of the most popular programming languages, created by Google. Go is much simpler than most other modern programming languages such as Java or C#. It is easier to learn. It is easier to use. And, it is more fun to use. If you are just starting with programming, then Go is the perfect language to learn programming with. Go is a backend programming language, and it is different from other popular dynamic languages like Python and Javascript. It requires more discipline. It will make you a better programmer. Once you are comfortable with Go, you can more easily learn other programming languages. The Art of Go - Basics starts from the absolute basics and moves on to more advanced topics. Although it is an introductory book, you will gain sufficient knowledge, after reading this book, that you can venture into a journey of programming in Go on your own. If you are a seasoned developer, then it will provide a good introduction to idiomatic usages of Go in broad contexts. Who is this book for? Anyone who wants to know what programming is and how the code is written. Anyone who has tried to learn programming and given up because it was too hard. Anyone who has some experience in programming and who wants to learn the Go language. The Art of Go - Basics is organized into a series of small lessons. Each lesson starts with simple example programs, and it emphasizes code reading rather than premature writing. You will learn basics of coding, and some intricacies of Golang, just by reading each lesson. The book includes some (optional) exercises, and it ends with a few final projects. The Art of Go - Basics covers the following topics (as of version Go 1.16), among other things: The basic structure of Go programs. Basic constructs of the Go programming language such as expressions and statements. Primitive types, slices, maps, and functions. Go structs, interfaces, and methods. Pointers. Value semantics vs reference semantics. Value receivers vs pointer receivers. Concurrent programming with Goroutines and channels. Simple network programming over TCP. Simple Web programming using the net/http standard package. Go build tools. Go modules. If you are just starting to learn programming, then learn Go. Learn programming with Go. The Art of Go - Basics will guide you through your first steps in the wonderful world of programming! Get this book now and start learning programming in Go today! |
| from math import sin: Beginning Python Peter C. Norton, Alex Samuel, Dave Aitel, Eric Foster-Johnson, Leonard Richardson, Jason Diamond, Aleatha Parker, Michael Roberts, 2005-07-08 This tutorial offers readers a thorough introduction to programming in Python 2.4, the portable, interpreted, object-oriented programming language that combines power with clear syntax Beginning programmers will quickly learn to develop robust, reliable, and reusable Python applications for Web development, scientific applications, and system tasks for users or administrators Discusses the basics of installing Python as well as the new features of Python release 2.4, which make it easier for users to create scientific and Web applications Features examples of various operating systems throughout the book, including Linux, Mac OS X/BSD, and Windows XP |
| from math import sin: Python Data Analytics Fabio Nelli, 2018-09-27 Explore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy, visualization with matplotlib, and machine learning with scikit-learn. This revision is fully updated with new content on social media data analysis, image analysis with OpenCV, and deep learning libraries. Each chapter includes multiple examples demonstrating how to work with each library. At its heart lies the coverage of pandas, for high-performance, easy-to-use data structures and tools for data manipulation Author Fabio Nelli expertly demonstrates using Python for data processing, management, and information retrieval. Later chapters apply what you've learned to handwriting recognition and extending graphical capabilities with the JavaScript D3 library. Whether you are dealing with sales data, investment data, medical data, web page usage, or other data sets, Python Data Analytics, Second Edition is an invaluable reference with its examples of storing, accessing, and analyzing data. What You'll LearnUnderstand the core concepts of data analysis and the Python ecosystem Go in depth with pandas for reading, writing, and processing data Use tools and techniques for data visualization and image analysis Examine popular deep learning libraries Keras, Theano,TensorFlow, and PyTorch Who This Book Is For Experienced Python developers who need to learn about Pythonic tools for data analysis |
| from math import sin: Python Essentials 2: Aligned with PCAP Certified Associate in Python Programming The OpenEDG Python Institute, 2023-08-22 Immerse yourself in some of the more advanced Python concepts, master Object-Oriented Programming, and gear up for the prestigious PCAP™ – Certified Associate Python Programmer certification. By the end of this book, you'll be equipped with the expertise to carry out more sophisticated Software Development, Security, Networking, IoT, and engineering roles. Additionally, this book will prepare you to tackle the PCAP qualification exam and take your programming skills to the next level. Being PCAP qualified means that both employers and your fellow programmers will be able to recognize your programming aptitude and rely on you to get jobs done. Python Essentials 2 takes you through some of the more advanced Python concepts and arms you with skills such as: Algorithmic and Analytical Thinking, to help you design and create your own applications Multi-Module Application Development and Debugging, to ensure that your coding skills are second-to-none Best Programming Practices of Python Professionals Solutions Architecture, so that you can successfully scale up your projects, collaborate with other programmers, and consistently deliver high-performing code Object-Oriented Programming, to ensure that your software is robust and adheres to the latest industry standards. This book builds upon your knowledge from Python Essentials 1, covering advanced techniques such as modules, packages, exceptions, file processing, and object-oriented programming. By learning these skills, you will become a proficient Python programmer and a valued member of the Python Programming Community, well-equipped to handle complex projects and codebases. With 24 chapters split into four parts, 22 lab exercises with hints and sample solutions and 23 quizzes, this book sets you on the path to becoming a certified python programmer. Elevate your coding prowess for future success; embark on your next Python journey now. |
| from math import sin: A Hands-On Introduction to Machine Learning Chirag Shah, 2022-12-31 Packed with real-world examples, industry insights and practical activities, this textbook is designed to teach machine learning in a way that is easy to understand and apply. It assumes only a basic knowledge of technology, making it an ideal resource for students and professionals, including those who are new to computer science. All the necessary topics are covered, including supervised and unsupervised learning, neural networks, reinforcement learning, cloud-based services, and the ethical issues still posing problems within the industry. While Python is used as the primary language, many exercises will also have the solutions provided in R for greater versatility. A suite of online resources is available to support teaching across a range of different courses, including example syllabi, a solutions manual, and lecture slides. Datasets and code are also available online for students, giving them everything they need to practice the examples and problems in the book. |
| from math import sin: Programming for Computations - Python Svein Linge, Hans Petter Langtangen, 2019-10-30 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. |
| from math import sin: Essential Programming for the Technical Artist Chris Roda, 2024-05-17 This book is based on a successful curriculum designed to elevate technical artists with no programming experience up to essential programming competency as quickly as possible. Instead of abstract, theoretical problems, the curriculum employs familiar applications encountered in real production environments to demonstrate each lesson. Written with artists in mind, this book introduces novice programmers to the advantageous world of Python programming with relevant and familiar examples. Any digital artists (not just technical artists) will find this book helpful in assisting with day-to-day production activities. Concentrating upon subjects relevant to the creation of computer graphic assets, this book introduces Python basics, functions, data types, object-oriented programming, exception handling, file processing, graphical user interface creation, PEP 8 standards, and regular expressions. Programming within the SideFX Houdini 3D animation software provides a familiar environment for artists to create and experiment with the covered Python topics. |
| from math import sin: Python Data Science Chaolemen Borjigin, 2023-06-30 Rather than presenting Python as Java or C, this textbook focuses on the essential Python programming skills for data scientists and advanced methods for big data analysts. Unlike conventional textbooks, it is based on Markdown and uses full-color printing and a code-centric approach to highlight the 3C principles in data science: creative design of data solutions, curiosity about the data lifecycle, and critical thinking regarding data insights. Q&A-based knowledge maps, tips and suggestions, notes, as well as warnings and cautions are employed to explain the key points, difficulties, and common mistakes in Python programming for data science. In addition, it includes suggestions for further reading. This textbook provides an open-source community via GitHub, and the course materials are licensed for free use under the following license: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0). |
| from math import sin: Modular Programming with Python Erik Westra, 2016-05-26 Introducing modular techniques for building sophisticated programs using Python About This Book The book would help you develop succinct, expressive programs using modular deign The book would explain best practices and common idioms through carefully explained and structured examples It will have broad appeal as far as target audience is concerned and there would be take away for all beginners to Python Who This Book Is For This book is intended for beginner to intermediate level Python programmers who wish to learn how to use modules and packages within their programs. While readers must understand the basics of Python programming, no knowledge of modular programming techniques is required. What You Will Learn Learn how to use modules and packages to organize your Python code Understand how to use the import statement to load modules and packages into your program Use common module patterns such as abstraction and encapsulation to write better programs Discover how to create self-testing Python packages Create reusable modules that other programmers can use Learn how to use GitHub and the Python Package Index to share your code with other people Make use of modules and packages that others have written Use modular techniques to build robust systems that can handle complexity and changing requirements over time In Detail Python has evolved over the years and has become the primary choice of developers in various fields. The purpose of this book is to help readers develop readable, reliable, and maintainable programs in Python. Starting with an introduction to the concept of modules and packages, this book shows how you can use these building blocks to organize a complex program into logical parts and make sure those parts are working correctly together. Using clearly written, real-world examples, this book demonstrates how you can use modular techniques to build better programs. A number of common modular programming patterns are covered, including divide-and-conquer, abstraction, encapsulation, wrappers and extensibility. You will also learn how to test your modules and packages, how to prepare your code for sharing with other people, and how to publish your modules and packages on GitHub and the Python Package Index so that other people can use them. Finally, you will learn how to use modular design techniques to be a more effective programmer. Style and approach This book will be simple and straightforward, focusing on imparting learning through a wide array of examples that the readers can put into use as they read through the book. They should not only be able to understand the way modules help in improving development, but they should also be able to improvise on their techniques of writing concise and effective code. |
| from math import sin: Practical WebGPU Graphics Jack Xu, 2021-06-11 WebGPU is the next-generation graphics API and future web standard for graphics and compute, aiming to provide modern 3D graphics and computation capabilities with the GPU acceleration. This book provides all the tools you need to help you create advanced 3D graphics and GPU computing on the web with this new WebGPU API. The book starts by taking you through the WebPack-TypeScript template for building the WebGPU apps and then shows you the WebGPU basics, shader program, GPU buffer, and rendering pipeline. Next, you will learn how to create primitives and simple objects in WebGPU. As you progress through the chapters, you will get to grips with advanced WebGPU topics, including 3D transformation, lighting calculation, colormaps, and textures. At the same time, you will learn how to create advanced 3D WebGPU objects, including various 3D wireframes, 3D shapes, simple and parametric 3D surfaces with colormaps and textures, as well as 3D surface plots and fractal graphics described by complex functions. In addition, you will explore new WebGPU features, such as compute shader and storage buffer, and how to use them to simulate large particle systems. By the end of this book, you will have the skill you need to build your own GPU-accelerated graphics and computing on the web with the WebGPU API. The book includes: - Template based on WebPack and TypeScript for developing WebGPU apps. - WebGPU basics, GLSL and WGSL shaders, and rendering pipeline. - Create primitives and simple shapes in WebGPU. - 3D transformations, model, viewing, projection, and various coordinate systems. - GPU buffers, uniform buffer objects, animation, and camera controls. - Normal vectors, lighting model, ambient, diffuse, and specular light calculations. - UV coordinates, texture mapping.- Color model, colormaps, and color interpolation. - Create 3D shapes, wireframes, surfaces, and 3D charts. - Create 3D plots and fractal graphics using complex functions. - Compute shaders, storage buffers, and large particle system simulation. |
| from math import sin: High Performance Python Micha Gorelick, Ian Ozsvald, 2014-08-22 Your Python code may run correctly, but you need it to run faster. By exploring the fundamental theory behind design choices, this practical guide helps you gain a deeper understanding of Python’s implementation. You’ll learn how to locate performance bottlenecks and significantly speed up your code in high-data-volume programs. How can you take advantage of multi-core architectures or clusters? Or build a system that can scale up and down without losing reliability? Experienced Python programmers will learn concrete solutions to these and other issues, along with war stories from companies that use high performance Python for social media analytics, productionized machine learning, and other situations. Get a better grasp of numpy, Cython, and profilers Learn how Python abstracts the underlying computer architecture Use profiling to find bottlenecks in CPU time and memory usage Write efficient programs by choosing appropriate data structures Speed up matrix and vector computations Use tools to compile Python down to machine code Manage multiple I/O and computational operations concurrently Convert multiprocessing code to run on a local or remote cluster Solve large problems while using less RAM |
| from math import sin: Cython Kurt W. Smith, 2015-01-21 Build software that combines Python’s expressivity with the performance and control of C (and C++). It’s possible with Cython, the compiler and hybrid programming language used by foundational packages such as NumPy, and prominent in projects including Pandas, h5py, and scikits-learn. In this practical guide, you’ll learn how to use Cython to improve Python’s performance—up to 3000x— and to wrap C and C++ libraries in Python with ease. Author Kurt Smith takes you through Cython’s capabilities, with sample code and in-depth practice exercises. If you’re just starting with Cython, or want to go deeper, you’ll learn how this language is an essential part of any performance-oriented Python programmer’s arsenal. Use Cython’s static typing to speed up Python code Gain hands-on experience using Cython features to boost your numeric-heavy Python Create new types with Cython—and see how fast object-oriented programming in Python can be Effectively organize Cython code into separate modules and packages without sacrificing performance Use Cython to give Pythonic interfaces to C and C++ libraries Optimize code with Cython’s runtime and compile-time profiling tools Use Cython’s prange function to parallelize loops transparently with OpenMP |
| from math import sin: A Course in Python Roozbeh Hazrat, 2024-01-04 This textbook introduces Python and its programming through a multitude of clearly presented examples and worked-out exercises. Based on a course taught to undergraduate students of mathematics, science, engineering and finance, the book includes chapters on handling data, calculus, solving equations, and graphics, thus covering all of the basic topics in Python. Each section starts with a description of a new topic and some basic examples. The author then demonstrates the new concepts through worked out exercises. The intention is to enable the reader to learn from the codes, thus avoiding lengthy, exhausting explanations. With its strong focus on programming and problem solving, and an emphasis on numerical problems that do not require advanced mathematics, this textbook is also ideal for self-study, for instance for researchers who wish to use Python as a computational tool. |
| from math import sin: Essential Python for the Physicist Giovanni Moruzzi, 2020-06-02 This book introduces the reader with little or no previous computer-programming experience to the Python programming language of interest for a physicist or a natural-sciences student. The book starts with basic interactive Python in order to acquire an introductory familiarity with the language, than tackle Python scripts (programs) of increasing complexity, that the reader is invited to run on her/his computer. All program listings are discussed in detail, and the reader is invited to experiment on what happens if some code lines are modified. The reader is introduced to Matplotlib graphics for the generation of figures representing data and function plots and, for instance, field lines. Animated function plots are also considered. A chapter is dedicated to the numerical solution of algebraic and transcendental equations, the basic mathematical principles are discussed and the available Python tools for the solution are presented. A further chapter is dedicated to the numerical solution of ordinary differential equations. This is of vital importance for the physicist, since differential equations are at the base of both classical physics (Newton’s equations) and quantum mechanics (Schroedinger’s equation). The shooting method for the numerical solution of ordinary differential equations with boundary conditions at two boundaries is also presented. Python programs for the solution of two quantum-mechanics problems are discussed as examples. Two chapters are dedicated to Tkinter graphics, which gives the user more freedom than Matplotlib, and to Tkinter animation. Programs displaying the animation of physical problems involving the solution of ordinary differential equations (for which in most cases there is no algebraic solution) in real time are presented and discussed. Finally, 3D animation is presented with Vpython. |
| from math import sin: Long Short-Term Memory Networks With Python Jason Brownlee, 2017-07-20 The Long Short-Term Memory network, or LSTM for short, is a type of recurrent neural network that achieves state-of-the-art results on challenging prediction problems. In this laser-focused Ebook, finally cut through the math, research papers and patchwork descriptions about LSTMs. Using clear explanations, standard Python libraries and step-by-step tutorial lessons you will discover what LSTMs are, and how to develop a suite of LSTM models to get the most out of the method on your sequence prediction problems. |
| from math import sin: Numerical Methods in Engineering with Python Jaan Kiusalaas, 2010-01-29 This text is for engineering students and a reference for practising engineers, especially those who wish to explore Python. This new edition features 18 additional exercises and the addition of rational function interpolation. Brent's method of root finding was replaced by Ridder's method, and the Fletcher-Reeves method of optimization was dropped in favor of the downhill simplex method. Each numerical method is explained in detail, and its shortcomings are pointed out. The examples that follow individual topics fall into two categories: hand computations that illustrate the inner workings of the method and small programs that show how the computer code is utilized in solving a problem. This second edition also includes more robust computer code with each method, which is available on the book website. This code is made simple and easy to understand by avoiding complex bookkeeping schemes, while maintaining the essential features of the method. |
| from math import sin: Introduction to the Tools of Scientific Computing Einar Smith, 2022-11-28 The book provides an introduction to common programming tools and methods in numerical mathematics and scientific computing. Unlike standard approaches, it does not focus on any specific language, but aims to explain the underlying ideas. Typically, new concepts are first introduced in the particularly user-friendly Python language and then transferred and extended in various programming environments from C/C++, Julia and MATLAB to Maple and Mathematica. This includes various approaches to distributed computing. By examining and comparing different languages, the book is also helpful for mathematicians and practitioners in deciding which programming language to use for which purposes. At a more advanced level, special tools for the automated solution of partial differential equations using the finite element method are discussed. On a more experimental level, the basic methods of scientific machine learning in artificial neural networks are explained and illustrated. |
| from math import sin: Python:A Kids and Hardware Engineer's Perspective Swapnil Sapre, 2012-10-25 This book explains my experiences in learning Python and implementing the same .And this topic-Python: A Kids and Hardware Engineer's Perspective - because not many books are targeted for this audience for the language in which I think is the easiest path to make your dreams into reality. Python must be the ideal choice for removing the hesitation to get into coding and make your hands dirty-this is the feeling which haunts both hardware engineers and kids equally for a programming language. |
| from math import sin: Dynamical Systems with Applications using Python Stephen Lynch, 2018-10-09 This textbook provides a broad introduction to continuous and discrete dynamical systems. With its hands-on approach, the text leads the reader from basic theory to recently published research material in nonlinear ordinary differential equations, nonlinear optics, multifractals, neural networks, and binary oscillator computing. Dynamical Systems with Applications Using Python takes advantage of Python’s extensive visualization, simulation, and algorithmic tools to study those topics in nonlinear dynamical systems through numerical algorithms and generated diagrams. After a tutorial introduction to Python, the first part of the book deals with continuous systems using differential equations, including both ordinary and delay differential equations. The second part of the book deals with discrete dynamical systems and progresses to the study of both continuous and discrete systems in contexts like chaos control and synchronization, neural networks, and binary oscillator computing. These later sections are useful reference material for undergraduate student projects. The book is rounded off with example coursework to challenge students’ programming abilities and Python-based exam questions. This book will appeal to advanced undergraduate and graduate students, applied mathematicians, engineers, and researchers in a range of disciplines, such as biology, chemistry, computing, economics, and physics. Since it provides a survey of dynamical systems, a familiarity with linear algebra, real and complex analysis, calculus, and ordinary differential equations is necessary, and knowledge of a programming language like C or Java is beneficial but not essential. |
| from math import sin: Python for Probability, Statistics, and Machine Learning José Unpingco, 2016-03-16 This book, fully updated for Python version 3.6+, covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. All the figures and numerical results are reproducible using the Python codes provided. The author develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes, thereby connecting theoretical concepts to concrete implementations. Detailed proofs for certain important results are also provided. Modern Python modules like Pandas, Sympy, Scikit-learn, Tensorflow, and Keras are applied to simulate and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, and regularization. Many abstract mathematical ideas, such as convergence in probability theory, are developed and illustrated with numerical examples. This updated edition now includes the Fisher Exact Test and the Mann-Whitney-Wilcoxon Test. A new section on survival analysis has been included as well as substantial development of Generalized Linear Models. The new deep learning section for image processing includes an in-depth discussion of gradient descent methods that underpin all deep learning algorithms. As with the prior edition, there are new and updated *Programming Tips* that the illustrate effective Python modules and methods for scientific programming and machine learning. There are 445 run-able code blocks with corresponding outputs that have been tested for accuracy. Over 158 graphical visualizations (almost all generated using Python) illustrate the concepts that are developed both in code and in mathematics. We also discuss and use key Python modules such as Numpy, Scikit-learn, Sympy, Scipy, Lifelines, CvxPy, Theano, Matplotlib, Pandas, Tensorflow, Statsmodels, and Keras. This book is suitable for anyone with an undergraduate-level exposure to probability, statistics, or machine learning and with rudimentary knowledge of Python programming. |
| from math import sin: Secret Recipes of the Python Ninja Cody Jackson, 2018-05-21 Test your Python programming skills by solving real-world problems Key Features Access built-in documentation tools and improve your code. Discover how to make the best use of decorator and generator functions Enhance speed and improve concurrency by conjuring tricks from the PyPy project Book Description This book covers the unexplored secrets of Python, delve into its depths, and uncover its mysteries. You’ll unearth secrets related to the implementation of the standard library, by looking at how modules actually work. You’ll understand the implementation of collections, decimals, and fraction modules. If you haven’t used decorators, coroutines, and generator functions much before, as you make your way through the recipes, you’ll learn what you’ve been missing out on. We’ll cover internal special methods in detail, so you understand what they are and how they can be used to improve the engineering decisions you make. Next, you’ll explore the CPython interpreter, which is a treasure trove of secret hacks that not many programmers are aware of. We’ll take you through the depths of the PyPy project, where you’ll come across several exciting ways that you can improve speed and concurrency. Finally, we’ll take time to explore the PEPs of the latest versions to discover some interesting hacks. What you will learn Know the differences between .py and .pyc files Explore the different ways to install and upgrade Python packages Understand the working of the PyPI module that enhances built-in decorators See how coroutines are different from generators and how they can simulate multithreading Grasp how the decimal module improves floating point numbers and their operations Standardize sub interpreters to improve concurrency Discover Python’s built-in docstring analyzer Who this book is for Whether you’ve been working with Python for a few years or you’re a seasoned programmer, you’ll have a lot of new tricks to walk away with. |
| from math import sin: Numerical Methods in Engineering with Python 3 Jaan Kiusalaas, 2013-01-21 This book is an introduction to numerical methods for students in engineering. It covers solution of equations, interpolation and data fitting, solution of differential equations, eigenvalue problems and optimisation. The algorithms are implemented in Python 3, a high-level programming language that rivals MATLAB® in readability and ease of use. All methods include programs showing how the computer code is utilised in the solution of problems. The book is based on Numerical Methods in Engineering with Python, which used Python 2. This new edition demonstrates the use of Python 3 and includes an introduction to the Python plotting package Matplotlib. This comprehensive book is enhanced by the addition of numerous examples and problems throughout. |
| from math import sin: Python Programming and Numerical Methods Qingkai Kong, Timmy Siauw, Alexandre Bayen, 2020-11-27 Python Programming and Numerical Methods: A Guide for Engineers and Scientists introduces programming tools and numerical methods to engineering and science students, with the goal of helping the students to develop good computational problem-solving techniques through the use of numerical methods and the Python programming language. Part One introduces fundamental programming concepts, using simple examples to put new concepts quickly into practice. Part Two covers the fundamentals of algorithms and numerical analysis at a level that allows students to quickly apply results in practical settings. - Includes tips, warnings and try this features within each chapter to help the reader develop good programming practice - Summaries at the end of each chapter allow for quick access to important information - Includes code in Jupyter notebook format that can be directly run online |
| from math import sin: Computational Partial Differential Equations Hans P. Langtangen, 2012-12-06 This text teaches finite element methods and basic finite difference methods from a computational point of view. It emphasizes developing flexible computer programs using the numerical library Diffpack, which is detailed for problems including model equations in applied mathematics, heat transfer, elasticity, and viscous fluid flow. This edition offers new applications and projects, and all program examples are available on the Internet. |
| from math import sin: Exploring Raspberry Pi Derek Molloy, 2016-06-09 Expand Raspberry Pi capabilities with fundamental engineering principles Exploring Raspberry Pi is the innovators guide to bringing Raspberry Pi to life. This book favors engineering principles over a 'recipe' approach to give you the skills you need to design and build your own projects. You'll understand the fundamental principles in a way that transfers to any type of electronics, electronic modules, or external peripherals, using a learning by doing approach that caters to both beginners and experts. The book begins with basic Linux and programming skills, and helps you stock your inventory with common parts and supplies. Next, you'll learn how to make parts work together to achieve the goals of your project, no matter what type of components you use. The companion website provides a full repository that structures all of the code and scripts, along with links to video tutorials and supplementary content that takes you deeper into your project. The Raspberry Pi's most famous feature is its adaptability. It can be used for thousands of electronic applications, and using the Linux OS expands the functionality even more. This book helps you get the most from your Raspberry Pi, but it also gives you the fundamental engineering skills you need to incorporate any electronics into any project. Develop the Linux and programming skills you need to build basic applications Build your inventory of parts so you can always make it work Understand interfacing, controlling, and communicating with almost any component Explore advanced applications with video, audio, real-world interactions, and more Be free to adapt and create with Exploring Raspberry Pi. |
| from math import sin: Introduction to Scientific Programming with Python Joakim Sundnes, 2020 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. |
| from math import sin: Beginning Python Visualization Shai Vaingast, 2014-08-28 We are visual animals. But before we can see the world in its true splendor, our brains, just like our computers, have to sort and organize raw data, and then transform that data to produce new images of the world. Beginning Python Visualization: Crafting Visual Transformation Scripts, Second Edition discusses turning many types of data sources, big and small, into useful visual data. And, you will learn Python as part of the bargain. In this second edition you’ll learn about Spyder, which is a Python IDE with MATLAB® -like features. Here and throughout the book, you’ll get detailed exposure to the growing IPython project for interactive visualization. In addition, you'll learn about the changes in NumPy and Scipy that have occurred since the first edition. Along the way, you'll get many pointers and a few visual examples. As part of this update, you’ll learn about matplotlib in detail; this includes creating 3D graphs and using the basemap package that allows you to render geographical maps. Finally, you'll learn about image processing, annotating, and filtering, as well as how to make movies using Python. This includes learning how to edit/open video files and how to create your own movie, all with Python scripts. Today's big data and computational scientists, financial analysts/engineers and web developers – like you - will find this updated book very relevant. |
| from math import sin: Programming with Python T R Padmanabhan, 2017-01-13 Based on the latest version of the language, this book offers a self-contained, concise and coherent introduction to programming with Python. The book’s primary focus is on realistic case study applications of Python. Each practical example is accompanied by a brief explanation of the problem-terminology and concepts, followed by necessary program development in Python using its constructs, and simulated testing. Given the open and participatory nature of development, Python has a variety of incorporated data structures, which has made it difficult to present it in a coherent manner. Further, some advanced concepts (super, yield, generator, decorator, etc.) are not easy to explain. The book specially addresses these challenges; starting with a minimal subset of the core, it offers users a step-by-step guide to achieving proficiency. |
| from math import sin: Let Us Python Kanetkar Yashavant, 2019-09-20 Learn Python Quickly, A Programmer-Friendly Guide Key features Strengthens the foundations, as detailed explanation of programming language concepts are given. Lists down all important points that you need to know related to various topics in an organized manner. Prepares you for coding related interview and theoretical questions. Provides In depth explanation of complex topics and Questions. Focuses on how to think logically to solve a problem. Follows systematic approach that will help you to prepare for an interview in short duration of time. Description Most Programmer's learning Python are usually comfortable with some or the other programming language and are not interested in going through the typical learning curve of learning the first programming language. Instead, they are looking for something that can get them off the ground quickly. They are looking for similarities and differences in a feature that they have used in other language(s). This book should help them immediately. It guides you from the fundamentals of using module through the use of advanced object orientation. What will you learn Data types, Control flow instructions, console & File Input/Output Strings, list & tuples, List comprehension Sets & Dictionaries, Functions & Lambdas Dictionary Comprehension Modules, classes and objects, Inheritance Operator overloading, Exception handling Iterators & Generators, Decorators, Command-line Parsing Who this book is forStudents, Programmers, researchers, and software developers who wish to learn the basics of Python programming language. Table of contents1. Introduction to Python2. Python Basics3. Strings4. Control Flow Instructions5. Console Input/Output6. Lists7. Tuples8. Sets9. Dictionaries10. Functions11. Modules12. Classes and Objects13. Intricacies of Classes and Objects14. Inheritance15. Exception Handling16. File Input/Output17. MiscellanyAbout the authorYashavant KanetkarThrough his books and Quest Video Courses on C, C++, Java, Python, Data Structures, .NET, IoT, etc. Yashavant Kanetkar has created, moulded and groomed lacs of IT careers in the last three decades. Yashavant's books and Quest videos have made a significant contribution in creating top-notch IT manpower in India and abroad. Yashavant's books are globally recognized and millions of students / professionals have benefitted from them. Yashavant's books have been translated into Hindi, Gujarati, Japanese, Korean and Chinese languages. Many of his books are published in India, USA, Japan, Singapore, Korea and China. Yashavant is a much sought after speaker in the IT field and has conducted seminars/workshops at TedEx, IITs, IIITs, NITs and global software companies. Yashavant has been honored with the prestigious e;Distinguished Alumnus Awarde; by IIT Kanpur for his entrepreneurial, professional and academic excellence. This award was given to top 50 alumni of IIT Kanpur who have made significant contribution towards their profession and betterment of society in the last 50 years. In recognition of his immense contribution to IT education in India, he has been awarded the e;Best .NET Technical Contributore; and e;Most Valuable Professionale; awards by Microsoft for 5 successive years. Yashavant holds a BE from VJTI Mumbai and M.Tech. from IIT Kanpur. Yadhavant's current affiliations include being a Director of KICIT Pvt Ltd. And KSET Pvt Ltd. His Linkedin profile: linkedin.com/in/yashavant-kanetkar-9775255 Aditya Kanetkar holds a Master's Degree in Computer Science from Georgia Tech, Atlanta. Prior to that, he completed his Bachelor's Degree in Computer Science and Engineering from IIT Guwahati. Aditya started his professional career as a Software Engineer at Oracle America Inc. at Redwood City, California. Currently he works with Microsoft Corp., USA. Aditya is a very keen programmer since his intern fays at Redfin, Amazon Inc. and Arista Networks. His current passion is anything remotely connected to Python, Machine Learning and C# related technologies. His Linkedin Profile: linkedin.com/in/aditya-kanetkar-a4292397 |
| from math import sin: An Introduction to Python and Computer Programming Yue Zhang, 2015-07-08 This book introduces Python programming language and fundamental concepts in algorithms and computing. Its target audience includes students and engineers with little or no background in programming, who need to master a practical programming language and learn the basic thinking in computer science/programming. The main contents come from lecture notes for engineering students from all disciplines, and has received high ratings. Its materials and ordering have been adjusted repeatedly according to classroom reception. Compared to alternative textbooks in the market, this book introduces the underlying Python implementation of number, string, list, tuple, dict, function, class, instance and module objects in a consistent and easy-to-understand way, making assignment, function definition, function call, mutability and binding environments understandable inside-out. By giving the abstraction of implementation mechanisms, this book builds a solid understanding of the Python programming language. |
| from math import sin: Artificial Intelligence and Robotics Shuo Yang, Huimin Lu, 2022-12-13 This two-volume set (CCIS 1700-1701) constitutes the refereed proceedings from the 7th International Symposium on Artificial Intelligence, ISAIR 2022, held in Shanghai, China, in October 2022. The 67 presented papers were thoroughly reviewed and selected from 285 submissions. The volumes present the state-of-the-art contributions on the cognitive intelligence, computer vision, multimedia, Internet of Things, robotics, and related applications. |
| from math import sin: Learning Geospatial Analysis with Python Joel Lawhead, 2023-11-24 Harness the powerful Python programming language to navigate the realms of geographic information systems, remote sensing, topography, and more, while embracing a guiding framework for effective geospatial analysis Key Features Create GIS solutions using the new features introduced in Python 3.10 Explore a range of GIS tools and libraries, including PostGIS, QGIS, and PROJ Identify the tools and resources that best align with your specific needs Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionGeospatial analysis is used in almost every domain you can think of, including defense, farming, and even medicine. In this special 10th anniversary edition, you'll embark on an exhilarating geospatial analysis adventure using Python. This fourth edition starts with the fundamental concepts, enhancing your expertise in geospatial analysis processes with the help of illustrations, basic formulas, and pseudocode for real-world applications. As you progress, you’ll explore the vast and intricate geospatial technology ecosystem, featuring thousands of software libraries and packages, each offering unique capabilities and insights. This book also explores practical Python GIS geospatial applications, remote sensing data, elevation data, and the dynamic world of geospatial modeling. It emphasizes the predictive and decision-making potential of geospatial technology, allowing you to visualize complex natural world concepts, such as environmental conservation, urban planning, and disaster management to make informed choices. You’ll also learn how to leverage Python to process real-time data and create valuable information products. By the end of this book, you'll have acquired the knowledge and techniques needed to build a complete geospatial application that can generate a report and can be further customized for different purposes.What you will learn Automate geospatial analysis workflows using Python Understand the different formats in which geospatial data is available Unleash geospatial tech tools to create stunning visualizations Create thematic maps with Python tools such as PyShp, OGR, and the Python Imaging Library Build a geospatial Python toolbox for analysis and application development Unlock remote sensing secrets, detect changes, and process imagery Leverage ChatGPT for solving Python geospatial solutions Apply geospatial analysis to real-time data tracking and storm chasing Who this book is for This book is for Python developers, researchers, or analysts who want to perform geospatial modeling and GIS analysis with Python. Basic knowledge of digital mapping and analysis using Python or other scripting languages will be helpful. |
| from math import sin: Python For Learners Ajit Singh, 2019-05-15 This text is an introduction to the world of the python. This book encapsulates rich practical hands-on experience in developing python based applications, combined with teaching the subject for graduate/post-graduate students. The book is therefore a culmination of putting together what has been both practiced as well as preached, which is the one of the most compelling differentiators for this book. It can also be used for independent study by anyone interested in getting a broad introduction to a core useful set of the python language. Python For Learners provides all essential programming concepts and information one shall need in order to start developing their own Python program. The book provides a comprehensive walk-through of Python programming in a clear, straightforward manner that beginners will appreciate. Important concepts are introduced through a step-by-step discussion and reinforced by relevant examples and illustrations. This book can be used as a guide to help explore, harness, and gain appreciation of the capabilities and features of Python. My approach in this book is to regard python as a language that readers will want to use as a primary tool in many different areas of their programming work - not just for creating programs with graphical content. Nevertheless, i recognize that visual examples are much more fun to create and work with. This book is a close-to-complete presentation of the Python language. It is oriented toward learning, which involves accumulating many closely intertwined concepts. In our experience teaching, coaching and doing programming, there is an upper limit on the clue absorption rate. In order to keep within this limit, i have found that it helps to present a language as ever-expanding layers. Well lead you from a very tiny, easy to understand subset of statements to the entire Python language and all of the built-in data structures. ● Ajit Singh |
| from math import sin: Probability for Machine Learning Jason Brownlee, 2019-09-24 Probability is the bedrock of machine learning. You cannot develop a deep understanding and application of machine learning without it. Cut through the equations, Greek letters, and confusion, and discover the topics in probability that you need to know. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover the importance of probability to machine learning, Bayesian probability, entropy, density estimation, maximum likelihood, and much more. |
| from math import sin: Developing Graphics Frameworks with Python and OpenGL Lee Stemkoski, Michael Pascale, 2021-07-06 Developing Graphics Frameworks with Python and OpenGL shows you how to create software for rendering complete three-dimensional scenes. The authors explain the foundational theoretical concepts as well as the practical programming techniques that will enable you to create your own animated and interactive computer-generated worlds. You will learn how to combine the power of OpenGL, the most widely adopted cross-platform API for GPU programming, with the accessibility and versatility of the Python programming language. Topics you will explore include generating geometric shapes, transforming objects with matrices, applying image-based textures to surfaces, and lighting your scene. Advanced sections explain how to implement procedurally generated textures, postprocessing effects, and shadow mapping. In addition to the sophisticated graphics framework you will develop throughout this book, with the foundational knowledge you will gain, you will be able to adapt and extend the framework to achieve even more spectacular graphical results. |
| from math import sin: Python and Algorithmic Thinking for the Complete Beginner Aristides Bouras, 2024-06-14 Unlock the power of Python with this comprehensive guide, “Python and Algorithmic Thinking for the Complete Beginner.” It covers everything from computer basics to advanced decision and loop control structures. Key Features Comprehensive coverage from basic computer operations to advanced programming concepts Step-by-step progression of each topic, along with tips and tricks to enhance coding efficiency In-depth exploration of Python and algorithmic thinking with exercises and practical examples Book DescriptionThis course is meticulously designed to take beginners on a journey through the fascinating world of Python programming and algorithmic thinking. The initial chapters lay a strong foundation, starting with the basics of how computers operate, moving into Python programming, and familiarizing learners with integrated development environments like IDLE and Visual Studio Code. Further, the course delves into essential programming constructs such as variables, constants, input/output handling, and operators. You'll gain practical experience with trace tables, sequence control structures, and decision control structures through comprehensive exercises and examples. The curriculum emphasizes hands-on learning with chapters dedicated to manipulating numbers, strings, and understanding complex mathematical expressions. By mastering these concepts, you'll be well-prepared to tackle more advanced topics. The final chapters introduce you to object-oriented programming and file manipulation, rounding out your skill set. Throughout the course, practical tips and tricks are provided to enhance your coding efficiency and problem-solving skills. By the end of this course, you will have a robust understanding of Python programming and the ability to apply algorithmic thinking to solve real-world problems.What you will learn Understand how computers work and the basics of Python programming Install and use integrated development environments (IDEs) Develop skills in decision and loop control structures Manipulate data using lists, dictionaries, and strings Apply algorithmic thinking to solve complex problems Gain proficiency in object-oriented programming & file manipulation Who this book is for This course is ideal for absolute beginners with no prior programming experience. Basic computer literacy is required, but no specific knowledge of programming or algorithms is necessary. It is also suitable for individuals looking to refresh their Python skills and enhance their understanding of algorithmic thinking. High school and college students interested in programming, professionals seeking to upskill, and hobbyists eager to learn a new programming language will all find value in this course. |
Math Study Resources - Answers
Math Delve into the study of matter, its properties, composition, structure, and the changes it undergoes during chemical reactions. Chemistry is the central science connecting other …
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Math and Arithmetic +2. What does slope measure? Asked by Anonymous. the rate of change in an object. Equation for slope is. Y2-Y1/X2-X1. A.K.A. The difference of the Y's over the …
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Nov 21, 2024 · Elephants have ivory tusks because ivory is a dense material that helps them maintain balance and stability. In a mathematical context, the joke may be a play on words, …
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Nov 4, 2024 · What does 60 mean in the bible? Very little as far as i can see. In Lev.27.3, a man between the age of 20 & 60 is worth 50 shekels for a vow, and a woman, 30 shekels. - (a …
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Apr 20, 2025 · In the Caribbean Examinations Council (CXC) grading system, a Grade 1 is typically awarded for scores ranging from 75% to 100%. This grade indicates a high level of …
Math Study Resources - Answers
Math Delve into the study of matter, its properties, composition, structure, and the changes it undergoes during chemical reactions. Chemistry is the central science connecting other …
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Math. Mathematics is an area of knowledge, which includes the study of such topics as numbers, formulas and related structures, shapes and spaces in which they are contained, and …
Answers - The Most Trusted Place for Answering Life's Questions
Math and Arithmetic +2. What does slope measure? Asked by Anonymous. the rate of change in an object. Equation for slope is. Y2-Y1/X2-X1. A.K.A. The difference of the Y's over the …
How long does it take to die from cutting a wrist? - Answers
Jan 24, 2025 · How long does it take to die after the wrist artery is cut? The time it takes to die after cutting the wrist artery can vary greatly depending on several factors, including the …
Why do elephant have ivory tusks math joke? - Answers
Nov 21, 2024 · Elephants have ivory tusks because ivory is a dense material that helps them maintain balance and stability. In a mathematical context, the joke may be a play on words, …
What day is the exact middle of the year? - Answers
Oct 2, 2024 · What day is halfway through the year? There are 365 days in a single year, so the middle of the year would be the 182.5 day of the year. July 1st is the 182nd day of the year …
Why did Pascal invent the first calculator in 1645? - Answers
Feb 6, 2025 · Continue Learning about Math & Arithmetic. What was the name of the second mechanical calculator invented in 1645 by Blaise Pascal? Pascaline. Is 1645 divisible by 5? …
All Topics - Answers
Geometry = Math of Euclid. Geometry is the Branch of math known for shapes (polygons), 3D figures, undefined terms, theorems, axioms, explanation of the universe, and pi. 330,616 …
What is 20 Shekels of Silver worth in Bible? - Answers
Nov 4, 2024 · What does 60 mean in the bible? Very little as far as i can see. In Lev.27.3, a man between the age of 20 & 60 is worth 50 shekels for a vow, and a woman, 30 shekels. - (a …
What percentage is considered a grade 1 in cxc? - Answers
Apr 20, 2025 · In the Caribbean Examinations Council (CXC) grading system, a Grade 1 is typically awarded for scores ranging from 75% to 100%. This grade indicates a high level of …
