Search results for "introduction to python programming"
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R 1,069.00
Tutorial Introduction to VHDL Programming
This book helps readers create good VHDL descriptions and simulate VHDL designs. It teaches VHDL using selected sample problems, which are solved step by step and with precise explanations, so that readers get a clear idea of what a good VHDL code should look like.The book is divided into eight chapters, covering aspects ranging from the very basics of VHDL syntax and the module concept, to VHDL logic circuit implementations. In the first chapter, the entity and architecture parts of a VHDL program are explained in detail. The second chapter explains the implementations of combinational logic circuits in VHDL language, while the following chapters offer information on the simulation of VHDL programs and demonstrate how to define data types other than the standard ones available in VHDL libraries. In turn, the fifth chapter explains the implementation of clocked sequential logic circuits, and the sixth shows the implementation of registers and counter packages. The book’s last two chapters detail how components, functions and procedures, as well as floating-point numbers, are implemented in VHDL. The book offers extensive exercises at the end of each chapter, inviting readers to learn VHDL by doing it and writing good code.
R 3,312.17
Introduction to Engineering Programming
Click here to read ACCU's review of this book.This text is an indispensable collection of four tutorials covering concepts in modern engineering computations, and engineering programming in ANSI C, MATLAB Version 5 and Java 1.1.
R 5,884.00
Introduction to Game Programming in C++
Introduction to Game Programming with C++ explores the world of game development with a focus on C++. This book begins with an explanation of the basics of mathematics as it relates to game programming, covers the fundamentals of C++, and describes a number of algorithms commonly used in games. In addition, it discusses several libraries that can help you manage graphics, add audio, and create installation software so you can get started on the path to making both 2D and 3D games.With this book understand the basics of programming in C++, including working with variables, constants, arrays, conditional statements, pointers, and functions; learn how to use the ClanLib library to make 2D games; discover how the OGRE graphics library can be used to implement particle systems and other effects in 3D games; find out how to integrate sound and music into your game.
R 1,323.00
Introduction to Java Programming and Data Structures, Global Edition
For courses in Java programming. A fundamentals-first approach. Introduction to Java Programming and Data Structures, Global Edition integrates programming, data structures and algorithms into 1 text. It takes a fundamentals-first approach, building a strong foundation of basic concepts and techniques before teaching object-oriented and advanced programming. Programming is explained in a problem-driven way that focuses on problem solving rather than syntax, illustrating concepts by example and providing many exercises with various levels of difficulty for practice. The 13th Edition reflects Java 18 technology and is completely revised in every detail to enhance clarity, content, examples and exercises.
R 3,546.00
Introduction to Sequential Monte Carlo
This book provides a general introduction to Sequential Monte Carlo (SMC) methods, also known as particle filters. These methods have become a staple for the sequential analysis of data in such diverse fields as signal processing, epidemiology, machine learning, population ecology, quantitative finance, and robotics.The coverage is comprehensive, ranging from the underlying theory to computational implementation, methodology, and diverse applications in various areas of science. This is achieved by describing SMC algorithms as particular cases of a general framework, which involves concepts such as Feynman-Kac distributions, and tools such as importance sampling and resampling. This general framework is used consistently throughout the book.Extensive coverage is provided on sequential learning (filtering, smoothing) of state-space (hidden Markov) models, as this remains an important application of SMC methods. More recent applications, such as parameter estimation of these models (through e.g. particle Markov chain Monte Carlo techniques) and the simulation of challenging probability distributions (in e.g. Bayesian inference or rare-event problems), are also discussed.The book may be used either as a graduate text on Sequential Monte Carlo methods and state-space modeling, or as a general reference work on the area. Each chapter includes a set of exercises for self-study, a comprehensive bibliography, and a “Python corner,” which discusses the practical implementation of the methods covered. In addition, the book comes with an open source Python library, which implements all the algorithms described in the book, and contains all the programs that were used to perform the numerical experiments.
R 1,842.51
R 2,345.32
R 456.00
Introduction to Computer Science
Introduction to Computer Science introduces students to the fundamentals of computer science by connecting the dots between applications they use every day and the underlying technologies that power them. Throughout, students learn valuable technical skills including how to write simple JavaScript programs, format a webpage with HTML and CSS code, reduce the size of a file, and more.Opening chapters of the text provide students with historical background, describe the numbering systems that computers operate with, and explain how computers store and convert data such as images and music. Later chapters explore the anatomy of computer hardware such as CPUs and memory, how computers communicate over networks, and the programming languages that allow us to solve problems using computation. The book concludes with chapters dedicated to security and privacy, the structure and function of operating systems, and the world of e-commerce.Accessible in approach, Introduction to Computer Science is designed to help non-computer science majors learn how technology and computers power the world around them. The text is well suited for introductory courses in computer science.
R 3,842.42
Practical Introduction to Fuzzy Logic using LISP
This book makes use of the LISP programming language to provide readers with the necessary background to understand and use fuzzy logic to solve simple to medium-complexity real-world problems. It introduces the basics of LISP required to use a Fuzzy LISP programming toolbox, which was specifically implemented by the author to “teach” the theory behind fuzzy logic and at the same time equip readers to use their newly-acquired knowledge to build fuzzy models of increasing complexity. The book fills an important gap in the literature, providing readers with a practice-oriented reference guide to fuzzy logic that offers more complexity than popular books yet is more accessible than other mathematical treatises on the topic. As such, students in first-year university courses with a basic tertiary mathematical background and no previous experience with programming should be able to easily follow the content. The book is intended for students and professionals in the fields of computer science and engineering, as well as disciplines including astronomy, biology, medicine and earth sciences. Software developers may also benefit from this book, which is intended as both an introductory textbook and self-study reference guide to fuzzy logic and its applications. The complete set of functions that make up the Fuzzy LISP programming toolbox can be downloaded from a companion book’s website.
R 4,315.16
Introduction to Reliable and Secure Distributed Programming
In modern computing a program is usually distributed among several processes. The fundamental challenge when developing reliable and secure distributed programs is to support the cooperation of processes required to execute a common task, even when some of these processes fail. Failures may range from crashes to adversarial attacks by malicious processes.Cachin, Guerraoui, and Rodrigues present an introductory description of fundamental distributed programming abstractions together with algorithms to implement them in distributed systems, where processes are subject to crashes and malicious attacks. The authors follow an incremental approach by first introducing basic abstractions in simple distributed environments, before moving to more sophisticated abstractions and more challenging environments. Each core chapter is devoted to one topic, covering reliable broadcast, shared memory, consensus, and extensions of consensus. For every topic, many exercises and their solutions enhance the understanding This book represents the second edition of "Introduction to Reliable Distributed Programming". Its scope has been extended to include security against malicious actions by non-cooperating processes. This important domain has become widely known under the name "Byzantine fault-tolerance".
R 3,866.79
Hands-On Introduction to Data Science
This book introduces the field of data science in a practical and accessible manner, using a hands-on approach that assumes no prior knowledge of the subject. The foundational ideas and techniques of data science are provided independently from technology, allowing students to easily develop a firm understanding of the subject without a strong technical background, as well as being presented with material that will have continual relevance even after tools and technologies change. Using popular data science tools such as Python and R, the book offers many examples of real-life applications, with practice ranging from small to big data. A suite of online material for both instructors and students provides a strong supplement to the book, including datasets, chapter slides, solutions, sample exams and curriculum suggestions. This entry-level textbook is ideally suited to readers from a range of disciplines wishing to build a practical, working knowledge of data science.
R 2,139.00
R 1,178.00
R 305.00
R 456.00
Introduction to the History of Computing
Tracing the story of computing from Babylonian counting boards to smartphones, this inspiring textbook provides a concise overview of the key events in the history of computing, together with discussion exercises to stimulate deeper investigation into this fascinating area. Features: provides chapter introductions, summaries, key topics, and review questions; includes an introduction to analogue and digital computers, and to the foundations of computing; examines the contributions of ancient civilisations to the field of computing; covers the first digital computers, and the earliest commercial computers, mainframes and minicomputers; describes the early development of the integrated circuit and the microprocessor; reviews the emergence of home computers; discusses the creation of the Internet, the invention of the smartphone, and the rise of social media; presents a short history of telecommunications, programming languages, operating systems, software engineering, artificial intelligence, and databases.
R 1,963.54
R 489.00
R 1,130.00
Introduction to R
The modern world is awash with data. The R Project is a statistical environment and programming language that can help to make sense of it all. A huge open-source project, R has become enormously popular because of its power and flexibility. With R you can organise, analyse and visualise data. This clear and methodical book will help you learn how to use R from the ground up, giving you a start in the world of data science.Learning about data is important in many academic and business settings, and R offers a potent and adaptable programming toolbox. The book covers a range of topics, including: importing/exporting data, summarising data, visualising data, managing and manipulating data objects, data analysis (regression, ANOVA and association among others) and programming functions. Regardless of your background or specialty, you'll find this book the perfect primer on data analysis, data visualisation and data management, and a springboard for further exploration.
R 1,934.00
Introduction to 3D Game Programming w DirectX11
This updated bestseller provides an introduction to programming interactive computer graphics, with an emphasis on game development using DirectX 11. The book is divided into three main parts: basic mathematical tools, fundamental tasks in Direct3D, and techniques and special effects. It includes new Direct3D 11 features such as hardware tessellation, the compute shader, dynamic shader linkage and covers advanced rendering techniques such as screen-space ambient occlusion, level-of-detail handling, cascading shadow maps, volume rendering, and character animation. Includes a companion CD-ROM with code and figures.eBook Customers: Companion files are available for downloading with order number/proof of purchase by writing to the publisher at info@merclearning.com.
R 1,277.00
Hands-On Financial Trading with Python
Learn algorithmic trading with Python by building one complete strategy, from market data to automated execution. Explore machine learning, AI signals, and rigorous backtestingKey FeaturesFollow one volatility tail-hedge strategy from market data to cloud deployment, and build more that show a real edgeExplore time-series models, machine learning, and AI-driven alpha signal generationChallenge backtests with walk-forward analysis and detect lookahead bias and overfittingBook DescriptionGo beyond learning Python libraries in isolation. This book teaches you the complete workflow professionals use to build systematic trading strategies.You start by acquiring, exploring, and cleaning market data, handling missing values, misaligned time series, and noise. From there, you form trading hypotheses, generate signals, and define entry and exit rules. You evaluate risk-adjusted performance and challenge your backtests through out-of-sample testing and walk-forward analysis. Next, you explore time-series models, machine learning for trading, and AI-driven alpha signal generation. Finally, you build a deployable strategy repository and automate execution in the cloud. One volatility tail-hedge strategy runs from raw data to cloud deployment, and you build five further strategies from published research, covering momentum, regime detection, economic indicators, and sector rotation, each tested to confirm that its signal does real work.Drawing on 25 years of institutional trading experience, the book shows you how to spot lookahead bias and overfitting and distinguish promising signals from noise. You work with VectorBT and QuantStats, with PythonAnywhere for deployment. The book includes all the code, and by the end you have working strategies and a repeatable framework for algorithmic trading with PythonWhat you will learnAcquire, clean, and denoise financial time-series dataUse exploratory analysis to develop trading hypothesesBuild momentum, mean-reversion, and time-series strategiesApply machine learning and AI to alpha signal generationValidate backtests with out-of-sample and walk-forward testingDetect lookahead bias, survivorship bias, and overfittingEvaluate strategies using risk-adjusted performance metricsBuild a deployable repository and automate cloud executionWho this book is forThis book is for traders going systematic, data scientists entering quantitative finance, and portfolio managers automating their workflows. Whether you are building your first complete strategy or moving beyond isolated Python scripts, you share one frustration: books that teach tools but not how to put them together. This book gives you that missing piece.You should be comfortable with basic Python, including functions, loops, and working in Jupyter notebooks, and with finance fundamentals such as returns, volatility, and risk.
R 1,628.00
Introduction to Data Science for Social and Policy Research
Real-world data sets are messy and complicated. Written for students in social science and public management, this authoritative but approachable guide describes all the tools needed to collect data and prepare it for analysis. Offering detailed, step-by-step instructions, it covers collection of many different types of data including web files, APIs, and maps; data cleaning; data formatting; the integration of different sources into a comprehensive data set; and storage using third-party tools to facilitate access and shareability, from Google Docs to GitHub. Assuming no prior knowledge of R and Python, the author introduces programming concepts gradually, using real data sets that provide the reader with practical, functional experience.
R 5,272.10
Practical Introduction to Fuzzy Logic using LISP
This book makes use of the LISP programming language to provide readers with the necessary background to understand and use fuzzy logic to solve simple to medium-complexity real-world problems. It introduces the basics of LISP required to use a Fuzzy LISP programming toolbox, which was specifically implemented by the author to “teach” the theory behind fuzzy logic and at the same time equip readers to use their newly-acquired knowledge to build fuzzy models of increasing complexity. The book fills an important gap in the literature, providing readers with a practice-oriented reference guide to fuzzy logic that offers more complexity than popular books yet is more accessible than other mathematical treatises on the topic. As such, students in first-year university courses with a basic tertiary mathematical background and no previous experience with programming should be able to easily follow the content. The book is intended for students and professionals in the fields of computer science and engineering, as well as disciplines including astronomy, biology, medicine and earth sciences. Software developers may also benefit from this book, which is intended as both an introductory textbook and self-study reference guide to fuzzy logic and its applications. The complete set of functions that make up the Fuzzy LISP programming toolbox can be downloaded from a companion book’s website.
R 3,873.51
Hands-On Introduction to Machine Learning
Packed with real-world examples, industry insights and practical activities, this textbook is designed to teach machine learning in a way that is easy to understand and apply. It assumes only a basic knowledge of technology, making it an ideal resource for students and professionals, including those who are new to computer science. All the necessary topics are covered, including supervised and unsupervised learning, neural networks, reinforcement learning, cloud-based services, and the ethical issues still posing problems within the industry. While Python is used as the primary language, many exercises will also have the solutions provided in R for greater versatility. A suite of online resources is available to support teaching across a range of different courses, including example syllabi, a solutions manual, and lecture slides. Datasets and code are also available online for students, giving them everything they need to practice the examples and problems in the book.
R 2,591.00
SymbolicC++:An Introduction to Computer Algebra using Object-Oriented Programming
Symbolic C++: An Introduction to Computer Algebra Using Object-Oriented Programming provides a concise introduction to C++ and object-oriented programming, using a step-by-step construction of a new object-oriented designed computer algebra system - Symbolic C++. It shows how object-oriented programming can be used to implement a symbolic algebra system and how this can then be applied to different areas in mathematics and physics. This second revised edition:- * Explains the new powerful classes that have been added to Symbolic C++. * Includes the Standard Template Library. * Extends the Java section. * Contains useful classes in scientific computation. * Contains extended coverage of Maple, Mathematica, Reduce and MuPAD.
R 1,619.40
R 611.00
R 885.00
R 762.00
Programming Arduino: Getting Started with Sketches, Third Edition
An up-to-date guide to Arduino programming—no experience required!This fully updated guide shows, step by step, how to quickly and easily program all Arduino models using its modified C language and the Arduino IDE. You will learn how to configure hardware and software, write your own sketches, work with built-in and custom Arduino libraries, and develop apps for the Internet of Things. This edition features new coverage of using Arduino as a framework for programming other popular boards.Electronics guru Simon Monk gets you up to speed quickly, teaching all concepts and syntax through simple language and clear instruction designed for absolute beginners. Programming Arduino: Getting Started with Sketches, Third Edition features dozens of easy-to-follow examples and high-quality illustrations. All of the sample sketches featured in the book can be used as-is or modified to suit the reader’s needs.Screenshots, diagrams, and source code illustrate each techniqueAll sample programs in the book are available for downloadWritten by a well-known hobbyist and experienced author
R 388.00
Introduction to Concurrency in Programming Languages
Exploring how concurrent programming can be assisted by language-level techniques, Introduction to Concurrency in Programming Languages presents high-level language techniques for dealing with concurrency in a general context. It provides an understanding of programming languages that offer concurrency features as part of the language definition.The book supplies a conceptual framework for different aspects of parallel algorithm design and implementation. It first addresses the limitations of traditional programming techniques and models when dealing with concurrency. The book then explores the current state of the art in concurrent programming and describes high-level language constructs for concurrency. It also discusses the historical evolution of hardware, corresponding high-level techniques that were developed, and the connection to modern systems, such as multicore and manycore processors. The remainder of the text focuses on common high-level programming techniques and their application to a range of algorithms. The authors offer case studies on genetic algorithms, fractal generation, cellular automata, game logic for solving Sudoku puzzles, pipelined algorithms, and more. Illustrating the effect of concurrency on programs written in familiar languages, this text focuses on novel language abstractions that truly bring concurrency into the language and aid analysis and compilation tools in generating efficient, correct programs. It also explains the complexity involved in taking advantage of concurrency with regard to program correctness and performance.
R 3,716.98
R 641.00
