Articles by "Programming"

Showing posts with label Programming. Show all posts

Saturday, April 06, 2024 , , ,
MATLAB R2024a v24.1.0.2537033 x64 [Size: 12.375 GB] ... The company MathWorks is the most complete software computing computer production in … program main the company that, in fact, come, it is software MATLAB (stands for Matrix Laboratory and able laboratories, matrix), which is one of the most advanced software numerical calculations, and mathematical and a programming language, advanced, and fourth-generation and it is possible to visualize and draw the functions and data it provides. Icon and sign MATLAB that with the manufacturer’s logo is also identical from the wave equation, etc. of the membrane in L-shape and the Special Functions is extracted. Competitors of MATLAB can be used to Mathematica, etc. Maple and Mathcad noted.

Facilities and features of the software MathWorks MATLAB: – Perform a variety of calculations, heavy and complicated math – Development environment for managing code, files and data – Discover the methods to faster reach a solution – A variety of mathematical functions for linear algebra, etc. statistics. analysis, February,, optimization, etc. filtering, etc. old style numeric and… – Draw functions of the graphics were two-dimensional and three-dimensional visualization information – Design and build user interfaces under the programming languages C++, C or Java – Ability to test and measure the exact functions and charts – Possibility of signal processing, communications, image and video – Is there a box of tools from various companies, engineering, navigation, applications monitoring, such as telecommunications, control, fuzzy, etc. estimate the … statistics. gathering data, simulation system, neural network, etc. probability and… – Ability to biological computing ...
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Sunday, January 21, 2024 , ,
David E. Clough, Steven C. Chapra ... Language: ‎English - Publisher: ‎CRC Press; (October, 2023).

Spreadsheet Problem Solving and Programming for Engineers and Scientists provides a comprehensive resource essential to a full understanding of modern spreadsheet skills needed for engineering and scientific computations.

Beginning with the basics of spreadsheets and programming, this book builds on the authors’ decades of experience teaching spreadsheets and programming to both university students and professional engineers and scientists. Following on from this, it covers engineering economics, key numerical methods, and applied statistics. Finally, this book details the Visual Basic for Applications (VBA) programming system that accompanies Excel.

With each chapter including examples and a set of exercises, this book is an ideal companion for all engineering courses and also for self-study. Based on the latest version of Excel (Microsoft Excel for Microsoft 365), it is also compatible with earlier versions of Excel dating back to Version 2013. Including numerous case studies, this book will be of interest to students and professionals working in all areas of engineering and science.
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Sunday, April 09, 2023 , ,
Makoto Sato ... 213 pages - Language: ‎English - Publisher: ‎Springer; (January, 2023) - ISBN-10: 9811982562 - ISBN-13: ‎978-9811982569.

This book helps the reader make use of the mathematical models of biological phenomena starting from the basics of programming and computer simulation. Computer simulations based on a mathematical model enable us to find a novel biological mechanism and predict an unknown biological phenomenon. Mathematical biology could further expand the progress of modern life sciences. Although many biologists are interested in mathematical biology, they do not have experience in mathematics and computer science. An educational course that combines biology, mathematics, and computer science is very rare to date. Published books for mathematical biology usually explain the theories of established mathematical models, but they do not provide a practical explanation for how to solve the differential equations included in the models, or to establish such a model that fits with a phenomenon of interest.

MATLAB is an ideal programming platform for the beginners of computer science. This book starts from the very basics about how to write a programming code for MATLAB (or Octave), explains how to solve ordinary and partial differential equations, and how to apply mathematical models to various biological phenomena such as diabetes, infectious diseases, and heartbeats. Some of them are original models, newly developed for this book. Because MATLAB codes are embedded and explained throughout the book, it will be easy to catch up with the text. In the final chapter, the book focuses on the mathematical model of the proneural wave, a phenomenon that guarantees the sequential differentiation of neurons in the brain. This model was published as a paper from the author’s lab (Sato et al., PNAS 113, E5153, 2016), and was intensively explained in the book chapter “Notch Signaling in Embryology and Cancer”, published by Springer in 2020. This book provides the reader who has a biological background with invaluable opportunities to learn and practice mathematical biology.
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Sunday, September 11, 2022 , ,
Peter Sestoft ... 341 pages - Publisher: Springer; 2nd edition (September, 2017) ... Language: English - ISBN-10: 331960788X - ISBN-13: 978-3319607887.

This book uses a functional programming language (F#) as a metalanguage to present all concepts and examples, and thus has an operational flavour, enabling practical experiments and exercises. It includes basic concepts such as abstract syntax, interpretation, stack machines, compilation, type checking, garbage collection, and real machine code. Also included are more advanced topics on polymorphic types, type inference using unification, co- and contravariant types, continuations, and backwards code generation with on-the-fly peephole optimization. This second edition includes two new chapters. One describes compilation and type checking of a full functional language, tying together the previous chapters. The other describes how to compile a C subset to real (x86) hardware, as a smooth extension of the previously presented compilers.The examples present several interpreters and compilers for toy languages, including compilers for a small but usable subset of C, abstract machines, a garbage collector, and ML-style polymorphic type inference. Each chapter has exercises. Programming Language Concepts covers practical construction of lexers and parsers, but not regular expressions, automata and grammars, which are well covered already. It discusses the design and technology of Java and C# to strengthen students’ understanding of these widely used languages.
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Sunday, June 05, 2022 , , ,
Wenyu Sun, Ya-Xiang Yuan ... 688 pages - Publisher: Springer; (May, 2006) ... Language: English - ISBN-10: 0387249753 - ISBN-13: 978-0387249759.

This book, a result of the author's teaching and research experience in various universities and institutes over the past ten years, can be used as a textbook for an optimization course for graduates and senior undergraduates. It systematically describes optimization theory and several powerful methods, including recent results. For most methods, the authors discuss an idea’s motivation, study the derivation, establish the global and local convergence, describe algorithmic steps, and discuss the numerical performance. The book deals with both theory and algorithms of optimization concurrently. It also contains an extensive bibliography. Finally, apart from its use for teaching, Optimization Theory and Methods will be very beneficial as a research reference.
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Sunday, April 10, 2022 , , ,
Cameron Davidson-Pilon  ... 256 pages - Publisher: ‎Addison-Wesley Professional; (October, 2015) - Language: English -  ISBN-10: 0133902838 - ISBN-13: 978-0133902839.

Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice–freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention.

Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You’ll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you’ve mastered these techniques, you’ll constantly turn to this guide for the working PyMC code you need to jumpstart future projects.

Coverage includes: • Learning the Bayesian “state of mind” and its practical implications • Understanding how computers perform Bayesian inference • Using the PyMC Python library to program Bayesian analyses • Building and debugging models with PyMC • Testing your model’s “goodness of fit” • Opening the “black box” of the Markov Chain Monte Carlo algorithm to see how and why it works • Leveraging the power of the “Law of Large Numbers” • Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning • Using loss functions to measure an estimate’s weaknesses based on your goals and desired outcomes • Selecting appropriate priors and understanding how their influence changes with dataset size • Overcoming the “exploration versus exploitation” dilemma: deciding when “pretty good” is good enough • Using Bayesian inference to improve A/B testing • Solving data science problems when only small amounts of data are available.
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Thursday, November 12, 2020 , , ,
Paul A. Zandbergen ... 420 pages - ISBN-10: 1589484991 - ISBN-13: 978-1589484993 ... Publisher: Esri Press; (July, 2020) - Language: English.

Python Scripting for ArcGIS Pro starts with the fundamentals of Python programming and then dives into how to write useful Python scripts that work with spatial data in ArcGIS Pro. Learn how to execute geoprocessing tools, describe, create and update data, as well as execute a number of specialized tasks. See how to write simple, custom scripts that will automate your ArcGIS Pro workflows.

Some of the key topics you will learn include: Python fundamentals + Setting up a Python editor + Automating geoprocessing tasks using ArcPy + Exploring and manipulating spatial and tabular data + Working with geometries using cursors + Working with rasters and map algebra + Map scripting + Debugging and error handling.

Helpful “points to remember,” key terms, and review questions are included at the end of each chapter to reinforce your understanding of Python. Corresponding data and exercises are available online. Whether you want to learn Python or already have some experience, Python Scripting for ArcGIS Pro is the comprehensive, hands-on book for learning the versatility of Python coding as an approach to solving problems and increasing your productivity in ArcGIS Pro. Follow the step-by-step instruction and common workflow guidance for automating tasks and scripting with Python.
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Friday, November 06, 2020 , ,
Slobodan Dmitrović ... 324 pages - ISBN-13: 978-1484260463 ... Publisher: Apress; (July, 2020) - Language: English.

Learn the C++ programming language in a structured, straightforward, and friendly manner. This book teaches the basics of the modern C++ programming language, C++ Standard Library, and modern C++ standards. No previous programming experience is required. C++ is a language like no other, surprising in its complexity, yet wonderfully sleek and elegant in so many ways. It is also a language that cannot be learned by guessing, one that is easy to get wrong and challenging to get right. To overcome this, each section is filled with real-world examples that gradually increase in complexity. Modern C++ for Absolute Beginners teaches more than just programming in C++20. It provides a solid C++ foundation to build upon.The author takes you through the C++ programming language, the Standard Library, and the C++11 to C++20 standard basics. Each chapter is accompanied by the right amount of theory and plenty of source code examples. You will work with C++20 features and standards, yet you will also compare and take a look into previous versions of C++. You will do so with plenty of relevant source code examples.

What You Will Learn: Work with the basics of C++: types, operators, variables, constants, expressions, references, functions, classes, I/O, smart pointers, polymorphism, and more + Set up the Visual Studio environment on Windows and GCC on Linux, where you can write your own code + Declare and define functions, classes, and objects, and organize code into namespaces + Discover object-oriented programming: classes and objects, encapsulation, inheritance, polymorphism, and more using the most advanced C++ features + Employ best practices in organizing source code and controlling program workflow + Get familiar with C++ language dos and donts, and more + Master the basics of lambdas, inheritance, polymorphism, smart pointers, templates, modules, contracts, concepts, and more. Who This Book Is For: Beginner or novice programmers who wish to learn C++ programming. No prior programming experience is required
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Thursday, August 27, 2020 , ,
Sulaymon L. Eshkabilov ... 495 pages - ISBN-10 : 1484257987 - ISBN-13 : 978-1484257982 ... Publisher : Apress; (April, 2020) - Language: : English.

Employ the essential and hands-on tools and functions of MATLAB's ordinary differential equation (ODE) and partial differential equation (PDE) packages, which are explained and demonstrated via interactive examples and case studies. This book contains dozens of simulations and solved problems via m-files/scripts and Simulink models which help you to learn programming and modeling of more difficult, complex problems that involve the use of ODEs and PDEs. You’ll become efficient with many of the built-in tools and functions of MATLAB/Simulink while solving more complex engineering and scientific computing problems that require and use differential equations. Practical MATLAB Modeling with Simulink explains various practical issues of programming and modelling.

After reading and using this book, you'll be proficient at using MATLAB and applying the source code from the book's examples as templates for your own projects in data science or engineering.
What You Will Learn: Model complex problems using MATLAB and Simulink + Gain the programming and modeling essentials of MATLAB using ODEs and PDEs + Use numerical methods to solve 1st and 2nd order ODEs + Solve stiff, higher order, coupled, and implicit ODEs + Employ numerical methods to solve 1st and 2nd order linear PDEs + Solve stiff, higher order, coupled, and implicit PDEs. Who This Book Is For: Engineers, programmers, data scientists, and students majoring in engineering, applied/industrial math, data science, and scientific computing. This book continues where Apress' Beginning MATLAB and Simulink leaves off.
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Sunday, July 12, 2020 , , ,
Zed Shaw ... 320 pages - Publisher: Addison-Wesley Professional; (June, 2017) ... Language: English - ISBN-10: 0134692888 - ISBN-13: 978-0134692883.

In Learn Python 3 the Hard Way, you’ll learn Python by working through 52 brilliantly crafted exercises. Read them. Type their code precisely. (No copying and pasting!) Fix your mistakes. Watch the programs run. As you do, you’ll learn how a computer works; what good programs look like; and how to read, write, and think about code. Zed then teaches you even more in 5+ hours of video where he shows you how to break, fix, and debug your code—live, as he’s doing the exercises.

Install a complete Python environment + Organize and write code + Fix and break code
Basic mathematics + Variables + Strings and text + Interact with users + Work with files + Looping and logic + Data structures using lists and dictionaries + Program design + Object-oriented programming + Inheritance and composition + Modules, classes, and objects + Python packaging + Automated testing + Basic game development + Basic web development.

It’ll be hard at first. But soon, you’ll just get it—and that will feel great! This course will reward you for every minute you put into it. Soon, you’ll know one of the world’s most powerful, popular programming languages. You’ll be a Python programmer.  This Book Is Perfect For: Total beginners with zero programming experience + Junior developers who know one or two languages + Returning professionals who haven’t written code in years + Seasoned professionals looking for a fast, simple, crash course in Python 3.
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Tuesday, July 07, 2020 , ,
Mark Fenner ... 592 pages - Publisher: Addison-Wesley Professional; (August, 2019) ... Language: English - ISBN-10: 0134845625 - ISBN-13: 978-0134845623.

The Complete Beginner’s Guide to Understanding and Building Machine Learning Systems with Python: Machine Learning with Python for Everyone will help you master the processes, patterns, and strategies you need to build effective learning systems, even if you’re an absolute beginner. If you can write some Python code, this book is for you, no matter how little college-level math you know. Principal instructor Mark E. Fenner relies on plain-English stories, pictures, and Python examples to communicate the ideas of machine learning. Mark begins by discussing machine learning and what it can do; introducing key mathematical and computational topics in an approachable manner; and walking you through the first steps in building, training, and evaluating learning systems. Step by step, you’ll fill out the components of a practical learning system, broaden your toolbox, and explore some of the field’s most sophisticated and exciting techniques. Whether you’re a student, analyst, scientist, or hobbyist, this guide’s insights will be applicable to every learning system you ever build or use.

Understand machine learning algorithms, models, and core machine learning concepts + Classify examples with classifiers, and quantify examples with regressors + Realistically assess performance of machine learning systems + Use feature engineering to smooth rough data into useful forms + Chain multiple components into one system and tune its performance + Apply machine learning techniques to images and text + Connect the core concepts to neural networks and graphical models + Leverage the Python scikit-learn library and other powerful tools.
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Thursday, July 02, 2020 , , ,
Lisa Oberbroeckling ... 296 pages - Publisher: Academic Press; (June, 2020) ... Language: English - ISBN-10: 0128177993 - ISBN-13: 978-0128177990.

Providing an alternative to engineering-focused resources in the area, Programming Mathematics Using MATLAB® introduces the basics of programming and of using MATLAB® by highlighting many mathematical examples. Emphasizing mathematical concepts through the visualization of programming throughout the book, this useful resource utilizes examples that may be familiar to math students (such as numerical integration) and others that may be new (such as fractals). Additionally, the text uniquely offers a variety of MATLAB® projects, all of which have been class-tested thoroughly, and which enable students to put MATLAB® programming into practice while expanding their comprehension of concepts such as Taylor polynomials and the Gram–Schmidt process. Programming Mathematics Using MATLAB® is appropriate for readers familiar with sophomore-level mathematics (vectors, matrices, multivariable calculus), and is useful for math courses focused on MATLAB® specifically and those focused on mathematical concepts which seek to utilize MATLAB® in the classroom.
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Thursday, June 25, 2020 , ,
Benjamin Bengfort, Rebecca Bilbro, Tony Ojeda ... 332 pages - Publisher: O'Reilly Media; (July, 2018) ... Language: English - ISBN-10: 1491963042 - ISBN-13: 978-1491963043.

From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it come in a constant stream, always changing and adapting in context; it also contains information that is not conveyed by traditional data sources. The key to unlocking natural language is through the creative application of text analytics. This practical book presents a data scientist’s approach to building language-aware products with applied machine learning. You’ll learn robust, repeatable, and scalable techniques for text analysis with Python, including contextual and linguistic feature engineering, vectorization, classification, topic modeling, entity resolution, graph analysis, and visual steering. By the end of the book, you’ll be equipped with practical methods to solve any number of complex real-world problems.

Preprocess and vectorize text into high-dimensional feature representations + Perform document classification and topic modeling + Steer the model selection process with visual diagnostics + Extract key phrases, named entities, and graph structures to reason about data in text + Build a dialog framework to enable chatbots and language-driven interaction + Use Spark to scale processing power and neural networks to scale model complexity.
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Tuesday, June 23, 2020 , , ,
Ryan Mitchell ... 308 pages - Publisher: O'Reilly Media; 2nd edition (April, 2018) ... Language: English - ISBN-10: 1491985577 - ISBN-13: 978-1491985571.

If programming is magic then web scraping is surely a form of wizardry. By writing a simple automated program, you can query web servers, request data, and parse it to extract the information you need. The expanded edition of this practical book not only introduces you web scraping, but also serves as a comprehensive guide to scraping almost every type of data from the modern web. Part I focuses on web scraping mechanics: using Python to request information from a web server, performing basic handling of the server’s response, and interacting with sites in an automated fashion. Part II explores a variety of more specific tools and applications to fit any web scraping scenario you’re likely to encounter. Parse complicated HTML pages + Develop crawlers with the Scrapy framework + Learn methods to store data you scrape + Read and extract data from documents + Clean and normalize badly formatted data + Read and write natural languages + Crawl through forms and logins + Scrape JavaScript and crawl through APIs + Use and write image-to-text software + Avoid scraping traps and bot blockers + Use scrapers to test your website.
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Tuesday, June 16, 2020 , ,
Ben Stephenson ... 219 pages - Publisher: Springer; 2nd edition (July, 2019) ... Language: English - ISBN-10: 3030188728 - ISBN-13: 978-3030188726.

This student-friendly textbook encourages the development of programming skills through active practice by focusing on exercises that support hands-on learning. The Python Workbook provides a compendium of 186 exercises, spanning a variety of academic disciplines and everyday situations. Solutions to selected exercises are also provided, supported by brief annotations that explain the technique used to solve the problem, or highlight a specific point of Python syntax. This enhanced new edition has been thoroughly updated and expanded with additional exercises, along with concise introductions that outline the core concepts needed to solve them. The exercises and solutions require no prior background knowledge, beyond the material covered in a typical introductory Python programming course.

Features: Uses an accessible writing style and easy-to-follow structure; includes a mixture of classic exercises from the fields of computer science and mathematics, along with exercises that connect to other academic disciplines; presents the solutions to approximately half of the exercises; provides annotations alongside the solutions, which explain the approach taken to solve the problem and relevant aspects of Python syntax; offers a variety of exercises of different lengths and difficulties; contains exercises that encourage the development of programming skills using if statements, loops, basic functions, lists, dictionaries, files, and recursive functions. Undergraduate students enrolled in their first programming course and wishing to enhance their programming abilities will find the exercises and solutions provided in this book to be ideal for their needs.
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Monday, May 25, 2020 , , ,
Svein Linge, Hans Petter Langtangen ... 216 pages - Publisher: Springer; (August, 2016) ... Language: English - AmazonSIN: B078YHJHL2.

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.
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Friday, May 01, 2020 , , ,
Edward B. Magrab, Shapour Azarm ... 848 pages - Publisher: Prentice Hall; 3rd edition (January, 2010) ... Language: English - ISBN-10: 0131991108 - ISBN-13: 978-0131991101.

An Engineer's Guide to MATLAB, is an authoritative guide to generating readable, compact, and verifiably correct MATLAB programs. It is ideal for undergraduate engineering courses in Mechanical, Aeronautical, Civil, and Electrical engineering that require/use MATLAB. This highly respected guide helps students develop a strong working knowledge of MATLAB that can be used to solve a wide range of engineering problems. Since solving these problems usually involves writing relatively short, one-time-use programs, the authors demonstrate how to effectively develop programs that are compact yet readable, easy to debug, and quick to execute. Emphasis is on using MATLAB to obtain solutions to several classes of engineering problems, so technical material is presented in summary form only.
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Tuesday, April 07, 2020 , , , ,
Laura Igual, Santi Segui ... 218 pages - Publisher: Springer; (March, 2017) ... Language: English - ISBN-10: 3319500163 - ISBN-13: 978-331950016.

This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis. Topics and features: provides numerous practical case studies using real-world data throughout the book; supports understanding through hands-on experience of solving data science problems using Python; describes techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming; reviews a range of applications of data science, including recommender systems and sentiment analysis of text data; provides supplementary code resources and data at an associated website.
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Monday, April 06, 2020 , , ,
John M. Stewart ... 230 pages - Publisher: Cambridge University Press; (August, 2014) ... Language: English - ISBN-10: 1107686423 - ISBN-13: 978-1107686427.

Python is a free, open source, easy-to-use software tool that offers a significant alternative to proprietary packages such as MATLAB and Mathematica. This book covers everything the working scientist needs to know to start using Python effectively. The author explains scientific Python from scratch, showing how easy it is to implement and test non-trivial mathematical algorithms and guiding the reader through the many freely available add-on modules. A range of examples, relevant to many different fields, illustrate the program's capabilities. In particular, readers are shown how to use pre-existing legacy code (usually in Fortran77) within the Python environment, thus avoiding the need to master the original code. Instead of exercises the book contains useful snippets of tested code which the reader can adapt to handle problems in their own field, allowing students and researchers with little computer expertise to get up and running as soon as possible.
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Sunday, April 05, 2020 , , ,
Micha Gorelick, Ian Ozsvald ... 370 pages- Publisher: O'Reilly Media; (September, 2014) ... Language: English - ISBN-10: 1449361595 - ISBN-13: 978-1449361594. 

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.
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