The use of Python as a powerful computational tool is expanding with great strides. Python is a language which is easy to use, and the libraries of tools provides it with efficient versatility. As the tools continue to expand, users can create insightful models and simulations. While the tools offer an easy method to create a pipeline, such constructions are not guaranteed to provide correct results. A lot of things can go wrong when building a simulation - deviously so. Users need to understand more than just how to build a process pipeline. Modeling and Simulation in Python introduces fundamental computational modeling techniques that are used in a variety of science and engineering disciplines. It emphasizes algorithmic thinking skills using different computational environments, and includes a number of interesting examples, including Shakespeare, movie databases, virus spread, and Chess. Key Features: Several theories and applications are provided, each with working Python scripts. All Python functions written for this book are archived on GitHub. Readers do not have to be Python experts, but a working knowledge of the language is required. Students who want to know more about the foundations of modeling and simulation will find this an educational and foundational resource.

Deep learning has transformed the fields of computer vision, image processing, and natural language applications. Thanks to TensorFlow.js, now JavaScript developers can build deep learning apps without relying on Python or R. Deep Learning with JavaScript shows developers how they can bring DL technology to the web. Written by the main authors of the TensorFlow library, this new book provides fascinating use cases and in-depth instruction for deep learning apps in JavaScript in your browser or on Node. Deploying computer vision, audio, and natural language processing in the browser Fine-tuning machine learning models with client-side data Constructing and training a neural network Interactive AI for browser games using deep reinforcement learning Generative neural networks to generate music and pictures TensorFlow.js is an open-source JavaScript library for defining, training, and deploying deep learning models to the web browser. It's quickly gaining popularity with developers for its amazing set of benefits including scalability, responsiveness, modularity, and portability. Shanging Cai and Eric Nielsen are senior software engineers on the Google Brain team. Stan Bileschi is the technical lead for Google's TensorFlow Usability team, which built the TensorFlow Layers API. All three have advanced degrees from MIT. Together, they're responsible for writing most of TensorFlow.js.

The C programming language is a popular language in industries as well as academics. Since its invention and standardized as ANSI C, several other standards known as C99, C11, and C17 were published with new features in subsequent years. This book covers all the traits of ANSI C and includes new features present in other standards. The content of this book helps a beginner to learn the fundamental concept of the C language. The book contains a step-by-step explanation of every program that allows a learner to understand the syntax and builds a foundation to write similar programs. The explanation clarity, exercises, and illustrations present in this book make it a complete textbook in all aspects. Features: Other than ANSI C, the book explains the new C standards like C99, C11, and C17. Most basic and easy-to-follow programs are chosen to explain the concepts and their syntax. More emphasis is given to the topics like Functions, Pointers, and Structures. Recursion is emphasized with numerous programming examples and diagrams. A separate chapter on the command-line argument and preprocessors is included that concisely explains their usage. Several real-life figures are taken to explain the concepts of dynamic memory allocation, file handling, and the difference between structure and union. The book contains more than 260 illustrations, more than 200 programs, and exercises at the end of each chapter. This book serves as a textbook for UG/PG courses in science and engineering. The researcher, postgraduate engineers, and embedded software developers can also keep this book as reference material for their fundamental learning.

Survival analysis uses statistics to calculate time to failure. Survival Analysis with Python takes a fresh look at this complex subject by explaining how to use the Python programming language to perform this type of analysis. As the subject itself is very mathematical and full of expressions and formulations, the book provides detailed explanations and examines practical implications. The book begins with an overview of the concepts underpinning statistical survival analysis. It then delves into Parametric models with coverage of Concept of maximum likelihood estimate (MLE) of a probability distribution parameter MLE of the survival function Common probability distributions and their analysis Analysis of exponential distribution as a survival function Analysis of Weibull distribution as a survival function Derivation of Gumbel distribution as a survival function from Weibull Non-parametric models including Kaplan-Meier (KM) estimator, a derivation of expression using MLE Fitting KM estimator with an example dataset, Python code and plotting curves Greenwood's formula and its derivation Models with covariates explaining The concept of time shift and the accelerated failure time (AFT) model Weibull-AFT model and derivation of parameters by MLE Proportional Hazard (PH) model Cox-PH model and Breslow's method Significance of covariates Selection of covariates The Python lifelines library is used for coding examples. By mapping theory to practical examples featuring datasets, this book is a hands-on tutorial as well as a handy reference.

How do you select the right programming language for the right job? Austin and Chancogne provide students with a collection of four tutorials that cover concepts in modern engineering computations, and engineering programming in Ansi C, Matlab Version 5, and Java 1.1. The text gives practical guidance on selecting the best programming language for a project through a large number of working examples. With the help of these examples, students will learn how to design, write, and execute engineering programs using these programming languages. By incorporating Ansi C, Matlab, and Java into one text, students will quickly learn the strengths and weaknesses of each language. They'll do this with the help of the 56 case study programs and 115 programming exercises integrated throughout the book. A small suite of basic engineering problems is also implemented in each of the three programming languages. The four tutorials featured in the book include:
* Modern Engineering Computations - covers hardware components in a simple computer, operating systems, networks (including the Internet and World Wide Web), and an overview of programming languages.
* C Tutorial - teaches students how to write multi-function C programs. Topics include basic data types, operators and expressions, program control, functions, dynamic memory allocation, and input/output.
* Matlab - shows students how to solve simple matrix programs with simple graphics. This tutorial also demonstrates how MATLAB programs can be much shorter than equivalent implementations in C or Java.
* Java - explains how Java got started, about object-oriented program design, and how to write Java programs with platform-independent graphical user interfaces that can operate across the Internet.

Recursion is one of the most fundamental concepts in computer science and a key programming technique that allows computations to be carried out repeatedly. Despite the importance of recursion for algorithm design, most programming books do not cover the topic in detail, despite the fact that numerous computer programming professors and researchers in the field of computer science education agree that recursion is difficult for novice students. Introduction to Recursive Programming provides a detailed and comprehensive introduction to recursion. This text will serve as a useful guide for anyone who wants to learn how to think and program recursively, by analyzing a wide variety of computational problems of diverse difficulty. It contains specific chapters on the most common types of recursion (linear, tail, and multiple), as well as on algorithm design paradigms in which recursion is prevalent (divide and conquer, and backtracking). Therefore, it can be used in introductory programming courses, and in more advanced classes on algorithm design. The book also covers lower-level topics related to iteration and program execution, and includes a rich chapter on the theoretical analysis of the computational cost of recursive programs, offering readers the possibility to learn some basic mathematics along the way. It also incorporates several elements aimed at helping students master the material. First, it contains a larger collection of simple problems in order to provide a solid foundation of the core concepts, before diving into more complex material. In addition, one of the book's main assets is the use of a step-by-step methodology, together with specially designed diagrams, for guiding and illustrating the process of developing recursive algorithms. Furthermore, the book covers combinatorial problems and mutual recursion. These topics can broaden students' understanding of recursion by forcing them to apply the learned concepts differently, or in a more sophisticated manner. The code examples have been written in Python 3, but should be straightforward to understand for students with experience in other programming languages. Finally, worked out solutions to over 120 end-of-chapter exercises are available for instructors.

Create Python packages to share your code in a scalable and maintainable way. Improve team productivity, publish helpful libraries, or even start your own open source project following the latest Python packaging standards. In Publishing Python Packages you will learn how to: Build extensions and console script commands Use tox to automate packaging, installing, and testing Build a continuous integration pipeline using GitHub Actions Improve code quality and reduce manual review using bandit, black, mypy, and radon Create published documentation for your packages Keep packages up to date with pyupgrade and Dependabot Foster an open source community using GitHub features Publishing Python Packages teaches you how to easily share your Python code with your team and the outside world. Learn a repeatable and highly automated process for package maintenance that's based on the best practices, tools, and standards of Python packaging. Whether you're entirely new to Python packaging or looking for optimal ways to maintain and scale your packages, this fast-paced and engaging guide is for you. about the technology Python packages are a great way to share your code and give a productivity boost to your colleagues and community. Whether you're reusing your code internally or contributing to open source, a properly automated system of packaging will save you from time-consuming manual maintenance. about the book Publishing Python Packages reveals best practices and standards for packaging your Python code in an easy, automated, and scalable way. The book walks you through creating a complete package, including a C extension, and guides you all the way to publishing on the Python Package Index. You'll get hands-on experience with the latest packaging tools, and learn the ins-and-outs of package testing and continuous integration. You'll even learn how to set up a successful open source project, including licensing, documentation, and nurturing a community of contributors.

Explaining cryptography and its mathematical issues in terms specifically designed to reach computer programmers, this book covers all that is needed to write professional level cryptographic code. An expanded and improved version of the very well received first edition, it includes approximately 100 pages of new material as well as numerous improvements in the original text. The CD-ROM features tools and programs for use with the text.

"It is the first book that I have read that makes STL quickly usable by working programmers" Francis Glassborow, Chair of The Association of C & C++ Users (ACCU) STL for C++ programmers Leen Ammeraal The Standard Template Library (STL) provides many useful and generally applicable programming tools. This book combines reference material and a well-paced tutorial to get you past the basics quickly. Small, complete programs illustrate the key STL features such as containers, algorithms, iterators and function objects. A section is devoted to the new string data type. All STL algorithms are formally presented by their prototypes and then informally described to show how to use them in practice. Concepts are well illustrated with a large number of example programs all of which are available via ftp (for access details please refer to the preface of the book or Wiley’s website). Finally, special examples are given to explain the advanced notions of function objects and function adaptors, including predicates, binders and negators.

For courses in Java Programming Layered, Back-to-Basics Approach to Java Programming This edition of Building Java Programs: A Back to Basics Approach uses a layered strategy to introduce Java programming and overcome the high failure rates that are common in introductory computer science courses. The authors' proven and class-tested "back to basics" approach introduces programming fundamentals first, with new syntax and concepts added over multiple chapters. Object-oriented programming is discussed only once students have developed a basic understanding of Java programming. Previous editions have established the text's reputation as an excellent choice for two-course sequences in introductory computer science, and new material in the 4th Edition incorporates concepts related to Java 8, functional programming, and image manipulation.

Maintaining a practical perspective, Python Programming: A Practical Approach acquaints you with the wonderful world of programming. The book is a starting point for those who want to learn Python programming. The backbone of any programming, which is the data structure and components such as strings, lists, etc., have been illustrated with many examples and enough practice problems to instill a level of self-confidence in the reader. Drawing on knowledge gained directly from teaching Computer Science as a subject and working on a wide range of projects related to ML, AI, deep learning, and blockchain, the authors have tried their best to present the necessary skills for a Python programmer. Once the foundation of Python programming is built and the readers are aware of the exact structure, dimensions, processing, building blocks, and representation of data, they can readily take up their specific problems from the area of interest and solve them with the help of Python. These include, but are not limited to, operators, control flow, strings, functions, module processing, object-oriented programming, exception and file handling, multithreading, synchronization, regular expressions, and Python database programming. This book on Python programming is specially designed to keep readers busy with learning fundamentals and generates a sense of confidence by attempting the assignment problems. We firmly believe that explaining any particular technology deviates from learning the fundamentals of a programming language. This book is focused on helping readers attempt implementation in their areas of interest through the skills imparted through this book. We have attempted to present the real essence of Python programming, which you can confidently apply in real life by using Python as a tool. Salient Features Based on real-world requirements and solution. Simple presentation without avoiding necessary details of the topic. Executable programs on almost every topic. Plenty of exercise questions, designed to test readers' skills and understanding. Purposefully designed to be instantly applicable, Python Programming: A Practical Approach provides implementation examples so that the described subject matter can be immediately implemented due to the well-known versatility of Python in handling different data types with ease.

API Design for C++ provides a comprehensive discussion of Application Programming Interface (API) development, from initial design through implementation, testing, documentation, release, versioning, maintenance, and deprecation. It is the only book that teaches the strategies of C++ API development, including interface design, versioning, scripting, and plug-in extensibility. Drawing from the author's experience on large scale, collaborative software projects, the text offers practical techniques of API design that produce robust code for the long term. It presents patterns and practices that provide real value to individual developers as well as organizations. API Design for C++ explores often overlooked issues, both technical and non-technical, contributing to successful design decisions that product high quality, robust, and long-lived APIs. It focuses on various API styles and patterns that will allow you to produce elegant and durable libraries. A discussion on testing strategies concentrates on automated API testing techniques rather than attempting to include end-user application testing techniques such as GUI testing, system testing, or manual testing. Each concept is illustrated with extensive C++ code examples, and fully functional examples and working source code for experimentation are available online. This book will be helpful to new programmers who understand the fundamentals of C++ and who want to advance their design skills, as well as to senior engineers and software architects seeking to gain new expertise to complement their existing talents. Three specific groups of readers are targeted: practicing software engineers and architects, technical managers, and students and educators.

A coherent and integrated account of the leading UML 2 semantics work and the practical applications of UML semantics development

With contributions from leading experts in the field, the book begins with an introduction to UML and goes on to offer in-depth and up-to-date coverage of:

The role of semantics

Considerations and rationale for a UML system model

Definition of the UML system model

UML descriptive semantics

Axiomatic semantics of UML class diagrams

The object constraint language

Axiomatic semantics of state machines

A coalgebraic semantic framework for reasoning about interaction designs

Semantics of activity diagrams

Verification of UML models

State invariants

Model transformation specification and verification

Additionally, readers are provided with expert guidance on how to resolve semantic problems and a section on applications of UML semantics with model analysis. "UML 2 Semantics and Applications" is an ideal resource for researchers and tool-builders working in UML, among others. It is also an excellent textbook for postgraduate teaching and research.

Master web app development with hands-on practice and video demonstration HTML5, JavaScript, and jQuery 24-Hour Trainer shows you how to build real-world HTML5 apps both web-based and mobile in combination with JavaScript, jQuery, and CSS/CSS3. You'll learn progressively more advanced skills as you work through the series of hands-on video lessons. Exercises and screencasts walk you step-by-step through the process of building web applications, and give you the opportunity to experiment and extend the examples to create your own working web app. You'll gain a solid understanding of the fundamental technologies, and develop a skillset that fully exploits the functionality of web development tools. Although HTML5 is at the forefront of web development, it exists within an ecosystem that also includes CSS/CSS3, JavaScript, and JavaScript libraries like jQuery. Building robust, functional web applications requires a clear understanding of these technologies, and more importantly, the manner in which they fit together. This is your step-by-step guide to building web apps, with a hands-on approach that helps you learn by doing. * Master the fundamentals of HTML and HTML5 * Explore multimedia capabilities and CSS3 * Integrate offline data storage, background processes, and other APIs * Adapt web applications for mobile phones and tablets Whether you're looking for a quick refresher or a first-time lesson, HTML5, JavaScript, and jQuery 24-Hour Trainer will quickly get you up to speed.

This book constitutes the refereed proceedings of the 13th International Conference on Evaluation of Novel Approaches to Software Engineering, ENASE 2018, held in Funchal, Madeira, Portugal, in March 2018. The 17 revised full papers and 5 revised short papers presented were carefully reviewed and selected from 95 submissions. The papers are organized in topical sections on service science and business information systems and software engineering.

This book constitutes the refereed proceedings of the 20th International Conference on Data Analytics and Management in Data Intensive Domains, DAMDID/RCDL 2018, held in Moscow, Russia, in October 2018.The 9 revised full papers presented together with three invited papers were carefully reviewed and selected from 54 submissions. The papers are organized in the following topical sections: FAIR data infrastructures, interoperability and reuse; knowledge representation; data models; data analysis in astronomy; text search and processing; distributed computing; information extraction from text.

This Festschrift volume is published in honor of Bernhard Steffen, Professor at the Technical University of Dortmund, on the occasion of his 60th birthday. His vision as well as his theoretical and practical work span the development and implementation of novel, specific algorithms, and the establishment of cross-community relationships with the effect to obtain simpler, yet more powerful solutions. He initiated many new lines of research through seminal papers that pioneered various fields, starting with the Concurrency Workbench, a model checking toolbox that significantly influenced the research and development of mode based high assurance systems worldwide. The contributions in this volume reflect the breadth and impact of his work. The introductory paper by the volume editors, the 23 full papers and two personal statements relate to Bernhard's research and life. This volume, the talks and the entire B-Day at ISoLA 2018 are a tribute to the first 30 years of Bernhard's passion, impact and vision for many facets of computer science in general and for formal methods in particular. Impact and vision include the many roles that formal methods-supported software development should play in education, in industry and in society.

This book is designed to cover the basics of C++, the powerful programming language used by developers all over the world. Its readily understandable concepts and easy syntax are used in video games, embedded systems, IoT devices, and resource-heavy AI applications. Using a "self-teaching" method with numerous examples and figures, the book covers all of the major C++ concepts, including pointers, classes, strings, arrays, polymorphism, inheritance, file handling, and more. Various types of the end of chapter exercises include theoretical, practical, and multiple choice (with answers) to enhance comprehension of the topics covered.

Description Xamarin is a toolset that allows users to write native mobile apps in C# and run them on both iOS and Android devices. Xamarin in Action teaches readers how to build Xamarin apps on iOS and Android from scratch while maximizing code re-use. By the end, readers will be able to build a high quality production-ready Xamarin app on iOS and Android from scratch with a high level of code reuse. Key Features * Layer-by-layer guide * Hands-on lessons * Teaches you to build production ready apps Audience This book is for C# developers with a few months through many years of experience who want to build native mobile apps for iOS and Android using the language and toolset they already know. About the technology Xamarin gives users the ability to share large portions of code across two platforms while still letting them write native apps that can take full advantage of the device and OS features specific to each platform. Jim Bennett is a Xamarin MVP, Microsoft MVP, Xamarin Certified Developer and an active community member. He's also a frequent speaker at events all around the world, including Xamarin user groups and Xamarin and Microsoft conferences. He regularly blogs about Xamarin development at https://jimbobbennett.io.

Learn the fundamentals of Python (3.7) and how to apply it to data science, programming, and web development. Fully updated to include hands-on tutorials and projects. Key Features Learn the fundamentals of Python programming with interactive projects Apply Python to data science with tools such as IPython and Jupyter Utilize Python for web development and build a real-world app using Django Book DescriptionLearn Python Programming is a quick, thorough, and practical introduction to Python - an extremely flexible and powerful programming language that can be applied to many disciplines. Unlike other books, it doesn't bore you with elaborate explanations of the basics but gets you up-and-running, using the language. You will begin by learning the fundamentals of Python so that you have a rock-solid foundation to build upon. You will explore the foundations of Python programming and learn how Python can be manipulated to achieve results. Explore different programming paradigms and find the best approach to a situation; understand how to carry out performance optimization and effective debugging; control the flow of a program; and utilize an interchange format to exchange data. You'll also walk through cryptographic services in Python and understand secure tokens. Learn Python Programming will give you a thorough understanding of the Python language. You'll learn how to write programs, build websites, and work with data by harnessing Python's renowned data science libraries. Filled with real-world examples and projects, the book covers various types of applications, and concludes by building real-world projects based on the concepts you have learned. What you will learn Get Python up and running on Windows, Mac, and Linux Explore fundamental concepts of coding using data structures and control flow Write elegant, reusable, and efficient code in any situation Understand when to use the functional or OOP approach Cover the basics of security and concurrent/asynchronous programming Create bulletproof, reliable software by writing tests Build a simple website in Django Fetch, clean, and manipulate data Who this book is forLearn Python Programming is for individuals with relatively little experience in coding or Python. It's also ideal for aspiring programmers who need to write scripts or programs to accomplish tasks. The book shows you how to create a full-fledged application.

This book constitutes the refereed proceedings of the 7th International Symposium on End-User Development, IS-EUD 2017, held in Hatfield, UK, in July 2019. The 9 full papers and 8 short papers presented were carefully reviewed and selected from 35 submissions. The papers discuss progress in research around end-user development through, or towards, methods, socio-technical environments, intelligent agents, as well as the most effective end-user programming paradigms for smart environments. Papers and submissions in all categories addressed this specific theme together with topics that have been traditionally covered by the broader themes of end-user development, such as domain specific tools, spreadsheets, educational applications, and end user aspects.

Just Enough R! An Interactive Approach to Machine Learning and Analytics presents just enough of the R language, machine learning algorithms, statistical methodology, and analytics for the reader to learn how to find interesting structure in data. The approach might be called "seeing then doing" as it first gives step-by-step explanations using simple, understandable examples of how the various machine learning algorithms work independent of any programming language. This is followed by detailed scripts written in R that apply the algorithms to solve nontrivial problems with real data. The script code is provided, allowing the reader to execute the scripts as they study the explanations given in the text. Features Gets you quickly using R as a problem-solving tool Uses RStudio's integrated development environment Shows how to interface R with SQLite Includes examples using R's Rattle graphical user interface Requires no prior knowledge of R, machine learning, or computer programming Offers over 50 scripts written in R, including several problem-solving templates that, with slight modification, can be used again and again Covers the most popular machine learning techniques, including ensemble-based methods and logistic regression Includes end-of-chapter exercises, many of which can be solved by modifying existing scripts Includes datasets from several areas, including business, health and medicine, and science About the Author Richard J. Roiger is a professor emeritus at Minnesota State University, Mankato, where he taught and performed research in the Computer and Information Science Department for over 30 years.

This fast-moving tutorial introduces you to OCaml, an industrial-strength programming language designed for expressiveness, safety, and speed. Through the book's many examples, you'll quickly learn how OCaml stands out as a tool for writing fast, succinct, and readable systems code using functional programming. Real World OCaml takes you through the concepts of the language at a brisk pace, and then helps you explore the tools and techniques that make OCaml an effective and practical tool. You'll also delve deep into the details of the compiler toolchain and OCaml's simple and efficient runtime system. This second edition brings the book up to date with almost a decade of improvements in the OCaml language and ecosystem, with new chapters covering testing, GADTs, and platform tooling. This title is also available as open access on Cambridge Core, thanks to the support of Tarides. Their generous contribution will bring more people to OCaml.

Construct, analyze, and visualize networks with networkx, a Python language module. Network analysis is a powerful tool you can apply to a multitude of datasets and situations. Discover how to work with all kinds of networks, including social, product, temporal, spatial, and semantic networks. Convert almost any real-world data into a complex network--such as recommendations on co-using cosmetic products, muddy hedge fund connections, and online friendships. Analyze and visualize the network, and make business decisions based on your analysis. If you're a curious Python programmer, a data scientist, or a CNA specialist interested in mechanizing mundane tasks, you'll increase your productivity exponentially. Complex network analysis used to be done by hand or with non-programmable network analysis tools, but not anymore! You can now automate and program these tasks in Python. Complex networks are collections of connected items, words, concepts, or people. By exploring their structure and individual elements, we can learn about their meaning, evolution, and resilience. Starting with simple networks, convert real-life and synthetic network graphs into networkx data structures. Look at more sophisticated networks and learn more powerful machinery to handle centrality calculation, blockmodeling, and clique and community detection. Get familiar with presentation-quality network visualization tools, both programmable and interactive--such as Gephi, a CNA explorer. Adapt the patterns from the case studies to your problems. Explore big networks with NetworKit, a high-performance networkx substitute. Each part in the book gives you an overview of a class of networks, includes a practical study of networkx functions and techniques, and concludes with case studies from various fields, including social networking, anthropology, marketing, and sports analytics. Combine your CNA and Python programming skills to become a better network analyst, a more accomplished data scientist, and a more versatile programmer. What You Need: You will need a Python 3.x installation with the following additional modules: Pandas (>=0.18), NumPy (>=1.10), matplotlib (>=1.5), networkx (>=1.11), python-louvain (>=0.5), NetworKit (>=3.6), and generalizesimilarity. We recommend using the Anaconda distribution that comes with all these modules, except for python-louvain, NetworKit, and generalizedsimilarity, and works on all major modern operating systems.