"Advanced Logo" shows how LOGO can be used as a vehicle to promote problem solving skills among secondary students, college students, and instructors. The book demonstrates the wide range of educational domains that can be explored through LOGO including generative grammars, physical laws of motion and mechanics, artificial intelligence, robotics, and calculus.

Learn how to program in modern C, from the basics through the advanced topics required for proficiency. This book is the fastest path to C fluency for anyone experienced in a general-purpose programming language. From start to finish, code examples highlight the idioms and best practices behind efficient, robust programs in a variety of areas. The book opens with a thorough coverage of syntax, built-in data types and operations, and program structure. C has quirks and presents challenges, which are covered in detail. The coverage of advanced features is what sets this book apart from others. Among the advanced topics covered are floating-point representation in the IEEE 754 standard; embedded assembly language in C code for overflow detection; regular expressions, assertions, and internationalization; WebAssembly through C; and software libraries for C and other clients. Memory efficiency and safety are the two major challenges in C programming, and you'll explore these challenges through a series of C examples. Arrays and structures, which are the means to high-level data representation, are covered in connection with pointers, which provide efficiency. The book again uses code examples in covering networking and wire-level security; concurrency (multiprocessing and multithreading); instruction-level parallelism; and interprocess communication through shared memory and files, pipes, message queues, and signals. Many books introduce C, but few also explain how to use it properly and optimally. Essential C does just that. What You'll Learn Accelerate your path to C mastery with this book for experienced programmers Refresh your approach to program structure and data types Dive into aggregates and pointers using modern C language Revisit storage classes and scope Dive into concurrency (multiprocessing and multithreading) and instruction-level parallelism Finish with regular expressions, assertions, signals, locales and more Who This Book Is For Professional programmers or software developers who has prior experience with C or in general wanting an accelerated learning guide to modern C programming language.

LogiQL is a new state-of-the-art programming language based on Datalog. It can be used to build applications that combine transactional, analytical, graph, probabilistic, and mathematical programming. LogiQL makes it possible to build hybrid applications that previously required multiple programming languages and databases. In this first book to cover LogiQL, the authors explain how to design, implement, and query deductive databases using this new programming language. LogiQL's declarative approach enables complex data structures and business rules to be simply specified and then automatically executed. It is especially suited to business applications requiring complex rules to be implemented efficiently, for example predictive analytics and supply chain optimization. Suitable for both novices and experienced developers, the book is written in easy-to-understand language. It includes many examples and exercises throughout to illustrate the main concepts and consolidate understanding.

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.

Build and deploy machine learning and deep learning models in production with end-to-end examples. This book begins with a focus on the machine learning model deployment process and its related challenges. Next, it covers the process of building and deploying machine learning models using different web frameworks such as Flask and Streamlit. A chapter on Docker follows and covers how to package and containerize machine learning models. The book also illustrates how to build and train machine learning and deep learning models at scale using Kubernetes. The book is a good starting point for people who want to move to the next level of machine learning by taking pre-built models and deploying them into production. It also offers guidance to those who want to move beyond Jupyter notebooks to training models at scale on cloud environments. All the code presented in the book is available in the form of Python scripts for you to try the examples and extend them in interesting ways. What You Will Learn Build, train, and deploy machine learning models at scale using Kubernetes Containerize any kind of machine learning model and run it on any platform using Docker Deploy machine learning and deep learning models using Flask and Streamlit frameworks Who This Book Is For Data engineers, data scientists, analysts, and machine learning and deep learning engineers

Developed from the author's many years of teaching computing courses, Programming in C++ for Engineering and Science guides students in designing programs to solve real problems encountered in engineering and scientific applications. These problems include radioactive decay, pollution indexes, digital circuits, differential equations, Internet addresses, data analysis, simulation, quality control, electrical networks, data encryption, beam deflection, and many other areas. To make it easier for novices to develop programs, the author uses an object-centered design approach that helps students identify the objects in a problem and the operations needed; develop an algorithm for processing; implement the objects, operations, and algorithm in a program; and test, correct, and revise the program. He also revisits topics in greater detail as the text progresses. By the end of the book, students will have a solid understanding of how C++ can be used to process complex objects, including how classes can be built to model objects. Web ResourceThe book's website at http://cs.calvin.edu/books/c++/engr-sci provides source code, expanded presentations, links to relevant sites, reference materials, lab exercises, and projects. For instructors, solutions to exercises and PowerPoint slides for classroom use are available upon qualifying course adoption.

With multicore processors now in every computer, server, and embedded device, the need for cost-effective, reliable parallel software has never been greater. By explaining key aspects of multicore programming, Fundamentals of Multicore Software Development helps software engineers understand parallel programming and master the multicore challenge. Accessible to newcomers to the field, the book captures the state of the art of multicore programming in computer science. It covers the fundamentals of multicore hardware, parallel design patterns, and parallel programming in C++, .NET, and Java. It also discusses manycore computing on graphics cards and heterogeneous multicore platforms, automatic parallelization, automatic performance tuning, transactional memory, and emerging applications. As computing power increasingly comes from parallelism, software developers must embrace parallel programming. Written by leaders in the field, this book provides an overview of the existing and up-and-coming programming choices for multicores. It addresses issues in systems architecture, operating systems, languages, and compilers.

C++ is now established as one of the leading industry programming languages for object-oriented software development. Its advantages over other languages include speed and flexibility. It is used as the base for many commercial software products and for performance solutions to complex problems. Not often taught as the primary programming language, students are frequently expected to pick up the language for themselves. This book is an ideal student self-learning guide.

As a step-by-step tutorial, this book teaches all language features and explains their practical usage. Intuitive examples are used that are neither too complex to distract, nor oversimplified. A key concept in C++ is programming with templates, which can help to program generic solutions - for example implementing polymorphism. Nicolai Josuttis teaches how to combine templates with object-oriented programming to produce the power of modern C++ development for high performance programs. It is a book that goes well beyond the basics.

A supplementary website, including source code, can be found at www.josuttis.com/cppbook

Features:

• comprehensive, detailed, readable, practical and up-to-date

• teaches how to get the power from C++, using the current ANSI language standard and programming mode

• specific hints help C and Java programmers switch and compare languages.

• website provides more examples and links to useful online resources.

This is the book for Gophers who want to learn how to build distributed systems. You know the basics of Go and are eager to put your knowledge to work. Build distributed services that are highly available, resilient, and scalable. This book is just what you need to apply Go to real-world situations. Level up your engineering skills today. Take your Go skills to the next level by learning how to design, develop, and deploy a distributed service. Start from the bare essentials of storage handling, then work your way through networking a client and server, and finally to distributing server instances, deployment, and testing. All this will make coding in your day job or side projects easier, faster, and more fun. Create your own distributed services and contribute to open source projects. Build networked, secure clients and servers with gRPC. Gain insights into your systems and debug issues with observable services instrumented with metrics, logs, and traces. Operate your own Certificate Authority to authenticate internal web services with TLS. Automatically handle when nodes are added or removed to your cluster with service discovery. Coordinate distributed systems with replicated state machines powered by the Raft consensus algorithm. Lay out your applications and libraries to be modular and easy to maintain. Write CLIs to configure and run your applications. Run your distributed system locally and deploy to the cloud with Kubernetes. Test and benchmark your applications to ensure they're correct and fast. Dive into writing Go and join the hundreds of thousands who are using it to build software for the real world. What You Need: Go 1.13+ and Kubernetes 1.16+

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.

What does a probabilistic program actually compute? How can one formally reason about such probabilistic programs? This valuable guide covers such elementary questions and more. It provides a state-of-the-art overview of the theoretical underpinnings of modern probabilistic programming and their applications in machine learning, security, and other domains, at a level suitable for graduate students and non-experts in the field. In addition, the book treats the connection between probabilistic programs and mathematical logic, security (what is the probability that software leaks confidential information?), and presents three programming languages for different applications: Excel tables, program testing, and approximate computing. This title is also available as Open Access on Cambridge Core.

This Element discusses how shiny, an R package, can help instructors teach quantitative methods more effectively by way of interactive web apps. The interactivity increases instructors' effectiveness by making students more active participants in the learning process, allowing them to engage with otherwise complex material in an accessible, dynamic way. The Element offers four detailed apps that cover two fundamental linear regression topics: estimation methods (least squares, maximum likelihood) and the classic linear regression assumptions. It includes a summary of what the apps can be used to demonstrate, detailed descriptions of the apps' full capabilities, vignettes from actual class use, and example activities. Two other apps pertain to a more advanced topic (LASSO), with similar supporting material. For instructors interested in modifying the apps, the Element also documents the main apps' general code structure, highlights some of the more likely modifications, and goes through what functions need to be amended.

Python is one of the most powerful, easy-to-read programming languages around, but it does have its limitations. This general purpose, high-level language that can be extended and embedded is a smart option for many programming problems, but a poor solution to others. Python For Dummies is the quick-and-easy guide to getting the most out of this robust program. This hands-on book will show you everything you need to know about building programs, debugging code, and simplifying development, as well as defining what actions it can perform. You'll wrap yourself around all of its advanced features and become an expert Python user in no time. This guide gives you the tools you need to:* Master basic elements and syntax* Document, design, and debug programs* Work with strings like a pro* Direct a program with control structures* Integrate integers, complex numbers, and modules* Build lists, stacks, and queues* Create an organized dictionary* Handle functions, data, and namespace* Construct applications with modules and packages* Call, create, extend, and override classes* Access the Internet to enhance your library* Understand the new features of Python 2.5 Packed with critical idioms and great resources to maximize your productivity, Python For Dummies is the ultimate one-stop information guide. In a matter of minutes you'll be familiar with Python's building blocks, strings, dictionaries, and sets; and be on your way to writing the program that you've dreamed about!

A practical guide to data mining using SQL and Excel Data Analysis Using SQL and Excel, 2nd Edition shows you how to leverage the two most popular tools for data query and analysis SQL and Excel to perform sophisticated data analysis without the need for complex and expensive data mining tools. Written by a leading expert on business data mining, this book shows you how to extract useful business information from relational databases. You'll learn the fundamental techniques before moving into the "where" and "why" of each analysis, and then learn how to design and perform these analyses using SQL and Excel. Examples include SQL and Excel code, and the appendix shows how non-standard constructs are implemented in other major databases, including Oracle and IBM DB2/UDB. The companion website includes datasets and Excel spreadsheets, and the book provides hints, warnings, and technical asides to help you every step of the way. Data Analysis Using SQL and Excel, 2nd Edition shows you how to perform a wide range of sophisticated analyses using these simple tools, sparing you the significant expense of proprietary data mining tools like SAS. * Understand core analytic techniques that work with SQL and Excel * Ensure your analytic approach gets you the results you need * Design and perform your analysis using SQL and Excel Data Analysis Using SQL and Excel, 2nd Edition shows you how to best use the tools you already know to achieve expert results.

Because of its portability and platform-independence, Java is the ideal computer programming language to use when working on graph algorithms and other mathematical programming problems. Collecting some of the most popular graph algorithms and optimization procedures, A Java Library of Graph Algorithms and Optimization provides the source code for a library of Java programs that can be used to solve problems in graph theory and combinatorial optimization. Self-contained and largely independent, each topic starts with a problem description and an outline of the solution procedure, followed by its parameter list specification, source code, and a test example that illustrates the usage of the code. The book begins with a chapter on random graph generation that examines bipartite, regular, connected, Hamilton, and isomorphic graphs as well as spanning, labeled, and unlabeled rooted trees. It then discusses connectivity procedures, followed by a paths and cycles chapter that contains the Chinese postman and traveling salesman problems, Euler and Hamilton cycles, and shortest paths. The author proceeds to describe two test procedures involving planarity and graph isomorphism. Subsequent chapters deal with graph coloring, graph matching, network flow, and packing and covering, including the assignment, bottleneck assignment, quadratic assignment, multiple knapsack, set covering, and set partitioning problems. The final chapters explore linear, integer, and quadratic programming. The appendices provide references that offer further details of the algorithms and include the definitions of many graph theory terms used in the book.

Gain the full understanding of today's digital world with the cohesive framework and logical organization found only in NEW PERSPECTIVES ON COMPUTER CONCEPTS 2016, ENHANCED, INTRODUCTORY. This dynamic book provides the latest updates on emerging technology with engaging learning features, informative visuals and hands-on activities proven to increase your understanding. An insightful introduction highlights today's digital evolution, while coverage of social media and online security examines concepts behind today's important trends in technology. You gain insights into the underlying principles supporting the wide scope of digital devices in use today with an emphasis on the connectivity that pervades modern life. This Enhanced Edition includes a new hands-on programming chapter that teaches you how to program using Python (TM).

Take advantage of Python to automate complex systems with readable code. This new edition will help you move from operations/system administration into easy-to-learn coding. You'll start by writing command-line scripts and automating simple DevOps-style tasks followed by creating reliable and fast unit tests designed to avoid incidents caused by buggy automation. You'll then move on to more advanced cases, like using Jupyter as an auditable remote-control panel and writing Ansible and Salt extensions. The updated information in this book covers best practices for deploying and updating Python applications. This includes Docker, modern Python packaging, and internal Python package repositories. You'll also see how to use the AWS API, and the Kubernetes API, and how to automate Docker container image building and running. Finally, you'll work with Terraform from Python to allow more flexible templating and customization of environments. What You'll Learn Understand operating system automation with Python Package Python applications Use Python as a DevOps console Review Cloud automation with Python Who This Book Is For DevOps engineer. Site Reliability Engineer, or similar (including Platform, Production, and Systems), and whose organization uses Python.

The Extreme Programming Pocket Guide covers XP assumptions, principles, events, artifacts, roles, and resources, and more. It concisely explains the relationships between the XP practices. If you want to adopt XP in stages, the Extreme Programming Pocket Guide will help you choose what to apply and when. Concise and easy to use, this handy pocket guide to XP is a must-have quick reference for anyone implementing a test-driven development environment.

Advanced Data Science and Analytics with Python enables data scientists to continue developing their skills and apply them in business as well as academic settings. The subjects discussed in this book are complementary and a follow-up to the topics discussed in Data Science and Analytics with Python. The aim is to cover important advanced areas in data science using tools developed in Python such as SciKit-learn, Pandas, Numpy, Beautiful Soup, NLTK, NetworkX and others. The model development is supported by the use of frameworks such as Keras, TensorFlow and Core ML, as well as Swift for the development of iOS and MacOS applications. Features: Targets readers with a background in programming, who are interested in the tools used in data analytics and data science Uses Python throughout Presents tools, alongside solved examples, with steps that the reader can easily reproduce and adapt to their needs Focuses on the practical use of the tools rather than on lengthy explanations Provides the reader with the opportunity to use the book whenever needed rather than following a sequential path The book can be read independently from the previous volume and each of the chapters in this volume is sufficiently independent from the others, providing flexibility for the reader. Each of the topics addressed in the book tackles the data science workflow from a practical perspective, concentrating on the process and results obtained. The implementation and deployment of trained models are central to the book. Time series analysis, natural language processing, topic modelling, social network analysis, neural networks and deep learning are comprehensively covered. The book discusses the need to develop data products and addresses the subject of bringing models to their intended audiences - in this case, literally to the users' fingertips in the form of an iPhone app. About the Author Dr. Jesus Rogel-Salazar is a lead data scientist in the field, working for companies such as Tympa Health Technologies, Barclays, AKQA, IBM Data Science Studio and Dow Jones. He is a visiting researcher at the Department of Physics at Imperial College London, UK and a member of the School of Physics, Astronomy and Mathematics at the University of Hertfordshire, UK.

A complete guide for the developer or student, this text provides an overview of general concepts and terminology, investigates the salient features of the reference processor, thoroughly explores the services and features of the reference RTOS, and culminates with a major case study. Perfect for embedded systems programmers, software engineers, electrical engineers, or firmware engineers with a programming background in C or C++.

The successful 30-Second series tackles coding, the science of programming the technology which operates in almost every aspect of modern life. Computer code operates behind nearly everything we do - from small calculations in the home to complex executions that drive the global economy. It influences who we see, follow, and like online and describes the websites we visit, the connections between them, the sounds heard on Spotify and videos watched on YouTube. There is very little we do which hasn't, in some way, been codified, analysed, and computed electronically, yet few of us possess a basic understanding of that ultimate language barrier. That's a shame, because coding is the key to so much. Simple programming concepts can explain plenty about the modern world and the changes to come in the age of AI. With insightful text edited by computer scientist and technology podcaster Mark Steadman and contributions from other industry experts, learn the origins of computer code, from the first computers developed in during the Industrial Revolution, through the codebreaking machines used during World War II to the hyperfast computers of the present day. Have all the key terms of this fascinating science explained in simple, bitesize chunks of information-rich text, as well as meeting the key figures who have helped make computer science what it is today. From algorithms and scripts to block-chain, bits and bots, turn to 30-Second Coding to reveal the secrets behind this fascinating subject.

An updated, innovative approach to data structures and algorithms

Written by an author team of experts in their fields, this authoritative guide demystifies even the most difficult mathematical concepts so that you can gain a clear understanding of data structures and algorithms in C++.

The unparalleled author team incorporates the object-oriented design paradigm using C++ as the implementation language, while also providing intuition and analysis of fundamental algorithms. Offers a unique multimedia format for learning the fundamentals of data structures and algorithmsAllows you to visualize key analytic concepts, learn about the most recent insights in the field, and "do" data structure designProvides clear approaches for developing programsFeatures a clear, easy-to-understand writing style that breaks down even the most difficult mathematical concepts

Building on the success of the first edition, this new version offers you an innovative approach to fundamental data structures and algorithms.

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.

Shading, as part of the creation of realistic computer-generated images, is currently bringing major advances to computer graphics, with important practical applications in computer game design and animation. Shaders are a more sophisticated way of making 3D objects look more realistic. While most shaders are created using proprietary shading languages, Sh, a new open-source system, simplifies the shader programming process by making it part of the C++ language. This book introduces Sh and describes how to program a GPU using C++ to implement both basic and advanced shading techniques. Readers of this book will be able to start writing advanced, modular shaders using Sh within a day