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Introduction to Linear Goal Programming
Provides a concise and lucid overview of the linear goal programming model, a computationally efficient algorithm for solution, duality and sensitivity analysis, and extensions of the methodology to integer as well as nonlinear models.
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Introduction to Quantum Computing with Q# and QDK
This book introduces the fundamentals of the theory of quantum computing, illustrated with code samples written in Q#, a quantum-specific programming language, and its related Quantum Development Kit. Quantum computing (QC) is a multidisciplinary field that sits at the intersection of quantum physics, quantum information theory, computer science and mathematics, and which may revolutionize the world of computing and software engineering. The book begins by covering historical aspects of quantum theory and quantum computing, as well as offers a gentle, algebra-based, introduction to quantum mechanics, specifically focusing on concepts essential for the field of quantum programming. Quantum state description, state evolution, quantum measurement and the Bell’s theorem are among the topics covered. The readers also get a tour of the features of Q# and familiarize themselves with the QDK. Next, the core QC topics are discussed, complete with the necessary mathematical formalism. This includes the notions of qubit, quantum gates and quantum circuits. In addition to that, the book provides a detailed treatment of a series of important concepts from quantum information theory, in particular entanglement and the no-cloning theorem, followed by discussion about quantum key distribution and its various protocols. Finally, the canon of most important QC algorithms and algorithmic techniques is covered in-depth - from the Deutsch-Jozsa algorithm, through Grover’s search, to Quantum Fourier Transform, quantum phase estimation and Shor’s algorithm. The book is an accessible introduction into the vibrant and fascinating field of quantum computing, offering a blend of academic diligence with pragmatism that is so central to software development world. All of the discussed theoretical aspects of QC are accompanied by runnable code examples, providing the reader with two different angles - mathematical and programmatic - of looking at the same problem space.
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Introduction To Machine Learning In Quantitative Finance, An
In today's world, we are increasingly exposed to the words 'machine learning' (ML), a term which sounds like a panacea designed to cure all problems ranging from image recognition to machine language translation. Over the past few years, ML has gradually permeated the financial sector, reshaping the landscape of quantitative finance as we know it.An Introduction to Machine Learning in Quantitative Finance aims to demystify ML by uncovering its underlying mathematics and showing how to apply ML methods to real-world financial data. In this book the authorsFeatured with the balance of mathematical theorems and practical code examples of ML, this book will help you acquire an in-depth understanding of ML algorithms as well as hands-on experience. After reading An Introduction to Machine Learning in Quantitative Finance, ML tools will not be a black box to you anymore, and you will feel confident in successfully applying what you have learnt to empirical financial data!The Python codes contained within An Introduction to Machine Learning in Quantitative Finance have been made publicly available on the author's GitHub: https://github.com/deepintomlf/mlfbook.git
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R 1,270.00
Introduction to Mechatronics
This textbook presents mechatronics through an integrated approach covering instrumentation, circuits and electronics, computer-based data acquisition and analysis, analog and digital signal processing, sensors, actuators, digital logic circuits, microcontroller programming and interfacing. The use of computer programming is emphasized throughout the text, and includes Matlab for system modeling, simulation, and analysis; LabVIEW for data acquisition and signal processing; and C++ for Arduino-based microcontroller programming and interfacing. Prof. Samanta provides numerous examples along with appropriate program codes, for simulation and analysis, that are discussed in detail to illustrate the concepts covered in each section. The book also includes the illustration of theoretical concepts through the virtual simulation platform Tinkercad to provide students virtual lab experience.
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Introduction to Dependent Types with Idris
Dependent types are a concept that allows developers to write proof-carrying code. Idris is a programming language that supports dependent types. This book will teach you the mathematical foundations of Idris as well as how to use it to write software and mathematically prove properties.The first part of the book serves as an introduction to the language's underlying theories. It starts by reviewing formal systems and mathematical logical systems as foundational building blocks, then gradually builds up to dependent types. Next, you'll learn type theory for dependent types. Following this, you'll explore the Idris programming language and conclude by exploring the depths of formal systems and type checkers by implementing them.Introduction to Dependent Types with Idris will walk you through simple examples through more advanced techniques, stepping up the difficulty as you gain more knowledge. Every chapter includes a set of exercises based on what it covered to further cement your learning. No specialized knowledge of mathematics is expected beyond the basics, so it is perfect for novices.What You Will Learn Understand Lambda calculus and dependent typesGain insight into functional programmingWrite mathematical proofs with IdrisWho This Book Is ForProgrammers, mathematicians, academics, and anyone else interested learning dependent types and lambda calculus.
R 997.28
Introduction To Numerical Computation, An
Developed during ten years of teaching experience, this book serves as a set of lecture notes for an introductory course on numerical computation, at the senior undergraduate level. These notes contain the material that can be covered in a semester, together with a few optional sections for additional reading. Rather than surveying a large number of algorithms, the book presents the most important computational methods and emphasizes the underlying mathematical ideas. In most chapters, graphs and drawings are relied on, to build up intuition. The notes are written in a rather colloquial style, presenting the subject matter in the same form as it can be explained in a classroom. For instructors, this will minimize the amount of effort required to prepare their blackboard presentations.As prerequisites, the book only relies on standard calculus, an introductory course on matrices, and some basic computer programming skills. As a new feature, these notes are supplemented by two sets of videos from the author's Youtube channel. These videos contain a complete set of live lectures given in Spring 2015, together with a complete set of short tutorials, from 5 to 15 minutes each.A set of homework problems is included at the end of each chapter. Homework projects cover a variety of applications, in connection with population dynamics, engineering, mechanics, image reconstruction, etc. A complete set of solutions is available for instructors, upon request.
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Introduction to Data Technologies
Providing key information on how to work with research data, Introduction to Data Technologies presents ideas and techniques for performing critical, behind-the-scenes tasks that take up so much time and effort yet typically receive little attention in formal education. With a focus on computational tools, the book shows readers how to improve their awareness of what tasks can be achieved and describes the correct approach to perform these tasks. Practical examples demonstrate the most important pointsThe author first discusses how to write computer code using HTML as a concrete example. He then covers a variety of data storage topics, including different file formats, XML, and the structure and design issues of relational databases. After illustrating how to extract data from a relational database using SQL, the book presents tools and techniques for searching, sorting, tabulating, and manipulating data. It also introduces some very basic programming concepts as well as the R language for statistical computing. Each of these topics has supporting chapters that offer reference material on HTML, CSS, XML, DTD, SQL, R, and regular expressions.One-stop shop of introductory computing information Written by a member of the R Development Core Team, this resource shows readers how to apply data technologies to tasks within a research setting. Collecting material otherwise scattered across many books and the web, it explores how to publish information via the web, how to access information stored in different formats, and how to write small programs to automate simple, repetitive tasks.
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Introduction to Bayesian Inference, Methods and Computation
These lecture notes provide a rapid, accessible introduction to Bayesian statistical methods. The course covers the fundamental philosophy and principles of Bayesian inference, including the reasoning behind the prior/likelihood model construction synonymous with Bayesian methods, through to advanced topics such as nonparametrics, Gaussian processes and latent factor models. These advanced modelling techniques can easily be applied using computer code samples written in Python and Stan which are integrated into the main text. Importantly, the reader will learn methods for assessing model fit, and to choose between rival modelling approaches.
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Introduction to Error Correcting Codes with Applications
5. 2 Rings and Ideals 148 5. 3 Ideals and Cyclic Subspaces 152 5. 4 Generator Matrices and Parity-Check Matrices 159 5. 5 Encoding Cyclic Codest 163 5. 6 Syndromes and Simple Decoding Procedures 168 5. 7 Burst Error Correcting 175 5. 8 Finite Fields and Factoring xn-l over GF(q) 181 5. 9 Another Method for Factoring xn-l over GF(q)t 187 5. 10 Exercises 193 Chapter 6 BCH Codes and Bounds for Cyclic Codes 6. 1 Introduction 201 6. 2 BCH Codes and the BCH Bound 205 6. 3 Bounds for Cyclic Codest 210 6. 4 Decoding BCH Codes 215 6. 5 Linearized Polynomials and Finding Roots of Polynomialst 224 6. 6 Exercises 231 Chapter 7 Error Correction Techniques and Digital Audio Recording 7. 1 Introduction 237 7. 2 Reed-Solomon Codes 237 7. 3 Channel Erasures 240 7. 4 BCH Decoding with Erasures 244 7. 5 Interleaving 250 7. 6 Error Correction and Digital Audio Recording 256 7.
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Introduction to Data Mining, Global Edition
Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each concept is explored thoroughly and supported with numerous examples. The text requires only a modest background in mathematics. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms.
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Introduction to Coding Theory
It is gratifying that this textbook is still sufficiently popular to warrant a third edition. I have used the opportunity to improve and enlarge the book. When the second edition was prepared, only two pages on algebraic geometry codes were added. These have now been removed and replaced by a relatively long chapter on this subject. Although it is still only an introduction, the chapter requires more mathematical background of the reader than the remainder of this book. One of the very interesting recent developments concerns binary codes defined by using codes over the alphabet 7l.4• There is so much interest in this area that a chapter on the essentials was added. Knowledge of this chapter will allow the reader to study recent literature on 7l. -codes. 4 Furthermore, some material has been added that appeared in my Springer Lec ture Notes 201, but was not included in earlier editions of this book, e. g. Generalized Reed-Solomon Codes and Generalized Reed-Muller Codes. In Chapter 2, a section on "Coding Gain" ( the engineer's justification for using error-correcting codes) was added. For the author, preparing this third edition was a most welcome return to mathematics after seven years of administration. For valuable discussions on the new material, I thank C.P.l.M.Baggen, I. M.Duursma, H.D.L.Hollmann, H. C. A. van Tilborg, and R. M. Wilson. A special word of thanks to R. A. Pellikaan for his assistance with Chapter 10.
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Introduction to Coding Theory
This book is designed to be usable as a textbook for an undergraduate course or for an advanced graduate course in coding theory as well as a reference for researchers in discrete mathematics, engineering and theoretical computer science. This second edition has three parts: an elementary introduction to coding, theory and applications of codes, and algebraic curves. The latter part presents a brief introduction to the theory of algebraic curves and its most important applications to coding theory.
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Mathematical Introduction to Linear Programming and Game Theory
Mathematical elegance is a constant theme in this treatment of linear programming and matrix games. Condensed tableau, minimal in size and notation, are employed for the simplex algorithm. In the context of these tableau the beautiful termination theorem of R.G. Bland is proven more simply than heretofore, and the important duality theorem becomes almost obvious. Examples and extensive discussions throughout the book provide insight into definitions, theorems, and applications. There is considerable informal discussion on how best to play matrix games. The book is designed for a one-semester undergraduate course. Readers will need a degree of mathematical sophistication and general tools such as sets, functions, and summation notation. No single college course is a prerequisite, but most students will do better with some prior college mathematics. This thorough introduction to linear programming and game theory will impart a deep understanding of the material and also increase the student's mathematical maturity.
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Introduction to Statistics Through Resampling Methods and R
A highly accessible alternative approach to basic statistics Praise for the First Edition: "Certainly one of the most impressive little paperback 200-page introductory statistics books that I will ever see . . . it would make a good nightstand book for every statistician."—Technometrics Written in a highly accessible style, Introduction to Statistics through Resampling Methods and R, Second Edition guides students in the understanding of descriptive statistics, estimation, hypothesis testing, and model building. The book emphasizes the discovery method, enabling readers to ascertain solutions on their own rather than simply copy answers or apply a formula by rote. The Second Edition utilizes the R programming language to simplify tedious computations, illustrate new concepts, and assist readers in completing exercises. The text facilitates quick learning through the use of: More than 250 exercises—with selected "hints"—scattered throughout to stimulate readers' thinking and to actively engage them in applying their newfound skills An increased focus on why a method is introduced Multiple explanations of basic concepts Real-life applications in a variety of disciplines Dozens of thought-provoking, problem-solving questions in the final chapter to assist readers in applying statistics to real-life applications Introduction to Statistics through Resampling Methods and R, Second Edition is an excellent resource for students and practitioners in the fields of agriculture, astrophysics, bacteriology, biology, botany, business, climatology, clinical trials, economics, education, epidemiology, genetics, geology, growth processes, hospital administration, law, manufacturing, marketing, medicine, mycology, physics, political science, psychology, social welfare, sports, and toxicology who want to master and learn to apply statistical methods.
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Introduction to 3D Game Programming with DirectX 12
This updated bestseller provides an introduction to programming interactive computer graphics, with an emphasis on game development using DirectX 12. The book is divided into three main parts: basic mathematical tools, fundamental tasks in Direct3D, and techniques and special effects. It shows how to use new Direct12 features such as command lists, pipeline state objects, descriptor heaps and tables, and explicit resource management to reduce CPU overhead and increase scalability across multiple CPU cores. The book covers modern special effects and techniques such as hardware tessellation, writing compute shaders, ambient occlusion, reflections, normal and displacement mapping, shadow rendering, and character animation. Includes a companion DVD 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.Features:Provides an introduction to programming interactive computer graphics, with an emphasis on game development using DirectX 12Uses new Direct3D 12 features to reduce CPU overhead and take advantage of multiple CPU coresContains detailed explanations of popular real-time game effectsIncludes a DVD with source code and all the images (including 4-color) from the bookLearn advance rendering techniques such as ambient occlusion, real-time reflections, normal and displacement mapping, shadow rendering, programming the geometry shader, and character animationCovers a mathematics review and 3D rendering fundamentals such as lighting, texturing, blending and stenciling Use the end-of-chapter exercises to test understanding and provide experience with DirectX 12
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Correctness-by-Construction Approach to Programming
The focus of this book is on bridging the gap between two extreme methods for developing software. On the one hand, there are texts and approaches that are so formal that they scare off all but the most dedicated theoretical computer scientists. On the other, there are some who believe that any measure of formality is a waste of time, resulting in software that is developed by following gut feelings and intuitions.Kourie and Watson advocate an approach known as “correctness-by-construction,” a technique to derive algorithms that relies on formal theory, but that requires such theory to be deployed in a very systematic and pragmatic way. First they provide the key theoretical background (like first-order predicate logic or refinement laws) that is needed to understand and apply the method. They then detail a series of graded examples ranging from binary search to lattice cover graph construction and finite automata minimization in order to show how it can be applied to increasingly complex algorithmic problems. The principal purpose of this book is to change the way software developers approach their task at programming-in-the-small level, with a view to improving code quality. Thus it coheres with both the IEEE’s Guide to the Software Engineering Body of Knowledge (SWEBOK) recommendations, which identifies themes covered in this book as part of the software engineer’s arsenal of tools and methods, and with the goals of the Software Engineering Method and Theory (SEMAT) initiative, which aims to “refound software engineering based on a solid theory.”
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Introduction to Data Structures and Algorithms
Data structures and algorithms are presented at the college level in a highly accessible format that presents material with one-page displays in a way that will appeal to both teachers and students. The thirteen chapters cover: Models of Computation, Lists, Induction and Recursion, Trees, Algorithm Design, Hashing, Heaps, Balanced Trees, Sets Over a Small Universe, Graphs, Strings, Discrete Fourier Transform, Parallel Computation. Key features: Complicated concepts are expressed clearly in a single page with minimal notation and without the "clutter" of the syntax of a particular programming language; algorithms are presented with self-explanatory "pseudo-code." * Chapters 1-4 focus on elementary concepts, the exposition unfolding at a slower pace. Sample exercises with solutions are provided. Sections that may be skipped for an introductory course are starred. Requires only some basic mathematics background and some computer programming experience. * Chapters 5-13 progress at a faster pace. The material is suitable for undergraduates or first-year graduates who need only review Chapters 1 -4. * This book may be used for a one-semester introductory course (based on Chapters 1-4 and portions of the chapters on algorithm design, hashing, and graph algorithms) and for a one-semester advanced course that starts at Chapter 5. A year-long course may be based on the entire book. * Sorting, often perceived as rather technical, is not treated as a separate chapter, but is used in many examples (including bubble sort, merge sort, tree sort, heap sort, quick sort, and several parallel algorithms). Also, lower bounds on sorting by comparisons are included with the presentation of heaps in the context of lower bounds for comparison-based structures. * Chapter 13 on parallel models of computation is something of a mini-book itself, and a good way to end a course. Although it is not clear what parallel
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Introduction to Java Through Game Development
Interested in learning how to program with Java? Let’s face it, the best way to learn to program is by writing programs. This can be a daunting proposition with the specter of hours of simple command line example programs hanging over your head. Fear not! Now you can learn to program in Java in a fun way by working on video games. With this book, you’ll get to work with three Java game projects and have access to the complete game code for each project, including a full Java game engine. After completing Introduction to Java through Game Development, you’ll be proficient in Java programming, having worked with the language’s fundamental aspects throughout the text, and will be ready to further your Java and game programming expertise with confidence.What You'llMaster the fundamentals of the Java programming languageUse different data structures like arrays, lists, stacks, and queuesUnderstand game programming basics including the main game loopGain experience working with three different game projects via the book’s coding challengesWork with the 2D game engine that powers the book's included games and learn to create your own new game projectsUnderstand advanced Java topics like classes, encapsulation, inheritance, and polymorphismWork with exceptions and how to use debugging techniques to trace through codeSharpen your skills with over a dozen coding challenges that test your abilities with a development task on a real game projectWho This Book Is ForThis book requires little to no programming experience to understand and benefit from the text.
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R 611.00
Practical Introduction to Pascal
Since the first edition of this book was written in 1977, there has been a tremendous increase in the use of Pascal. This increased use has had two significant effects. (1) It has produced a bett er understanding of the facilities of Pascal and their use. (2) It has fostered the production of the ISO standard for Pascal. This second edition reflects both this better understanding and the clarifications and changes to Pascal which have resulted from the production of the BSljlSO Pascal standard. The standard (BS 6192, which supplies the technical content for ISO 7185) is the definitive document on Pascal. My work on the Pascal standard has convinced me that the description of a programming language may be tutorial, or it may be definitive, or it may be neither! The chapters of this book do not constitute a definitive description of Pascal. They are essentially tutorial. The book is based on an introductory lecture course given at Manchester. In addition to lectures, the course consists of two kinds of practical work. The first is based on the solution of short pencil-and-paper exercises. The second requires the student to write complete programs and run them using interactive computer terminals. Each chapter of the book concludes with exercises and problems suitable forthese purposes. Although solutions to all of these are not presented in the book, teaching staff may obtain them by application to the authors.
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R 274.00
Introduction to Photoshop
This full-color book is an essential guide to getting started with Adobe Photoshop. It's packed with tutorials, illustrations, and practical exercises to help you make sense of this complex and powerful software.You'll start with the basics of Photoshop, including an overview of its myriad tools and other options. Next, you will learn about some of the common tasks that can be performed in Photoshop, such as how to touch up images and basic applications in photography. You'll also be walked through how to leverage Photoshop for special and 3D effects. Each and every technique author Kevin Wilson presents is illustrated step-by-step using screenshots with concise, easy to follow text. Downloadable sample photoshop files and images are also provided, to help you work your way through the book.Whether you are a graphic design student, a photographer, or just a keen computer user, this book will provide you with a firm grasp of the underpinning foundations of Photoshop and equip you with the skills needed to unleash its full power.What You Will LearnUnderstand Photoshop's many toolsUse Photoshop to execute common image manipulation tasks Touch up photographs and other images in PhotoshopRemove lens distortion and make photos look more professionalWho This Book Is ForStudents, those interested in starting graphic design, and photographers looking to enhance, clean up and manipulate their photos. No experience with image-manipulation software is needed.
R 866.00
Introduction to Numerical Computation in Pascal
Our intention in this book is to cover the core material in numerical analysis normally taught to students on degree courses in computer science. The main emphasis is placed on the use of analysis and programming techniques to produce well-designed, reliable mathematical software. The treatment should be of interest also to students of mathematics, science and engineering who wish to learn how to write good programs for mathematical computations. The reader is assumed to have some acquaintance with Pascal programming. Aspects of Pascal particularly relevant to numerical computation are revised and developed in the first chapter. Although Pascal has some drawbacks for serious numerical work (for example, only one precision for real numbers), the language has major compensating advantages: it is a widely used teaching language that will be familiar to many students and it encourages the writing of clear, well structured programs. By careful use of structure and documentation, we have produced codes that we believe to be readable; particular care has been taken to ensure that students should be able to understand the codes in conjunction with the descriptive material given in the book.
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Introduction to Compilers and Language Design
A compiler translates a program written in a high level language into a program written in a lower level language. For students of computer science, building a compiler from scratch is a rite of passage: a challenging and fun project that offers insight into many different aspects of computer science, some deeply theoretical, and others highly practical. This book offers a one semester introduction into compiler construction, enabling the reader to build a simple compiler that accepts a C-like language and translates it into working X86 or ARM assembly language. It is most suitable for undergraduate students who have some experience programming in C, and have taken courses in data structures and computer architecture.
R 762.00
Introduction to Prescriptive AI
Gain a working knowledge of prescriptive AI, its history, and its current and future trends. This book will help you evaluate different AI-driven predictive analytics techniques and help you incorporate decision intelligence into your business workflow through real-world examples.The book kicks off with an introduction to decision intelligence and provides insight into prescriptive AI and how it can be woven into various business strategies and frameworks. You'll then be introduced to different decision intelligence methodologies and how to implement them, along with advantages and limitations of each. Digging deeper, the authors then walk you through how to perform simulations and interpret the results. A full chapter is devoted to embedding decision intelligence processes and outcomes into your business workflow using various applications. The book concludes by exploring different cognitive biases humans are prone to, and how those biases can be eliminated by combining machine and human intelligence.Upon completing this book, you will understand prescriptive AI, tools, and techniques and will be ready to incorporate them into your business workflow.What You Will LearnImplement full-fledged decision intelligence applications using PythonLeverage the tools, techniques, and methodologies for prescriptive AIUnderstand how prescriptive AI can be used in different domains through practical examplesInterpret results and integrate them into your decision makingWho This Book Is ForData Scientists and Machine Learning Engineers, as well as business professionals who want to understand how AI-driven decision intelligence can help grow their business.
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Introduction to Languages, Machines and Logic
A well-written and accessible introduction to the most important features of formal languages and automata theory. It focuses on the key concepts, illustrating potentially intimidating material through diagrams and pictorial representations, and this edition includes new and expanded coverage of topics such as: reduction and simplification of material on Turing machines; complexity and O notation; propositional logic and first order predicate logic. Aimed primarily at computer scientists rather than mathematicians, algorithms and proofs are presented informally through examples, and there are numerous exercises (many with solutions) and an extensive glossary.
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R 458.00
Introduction to HPC with MPI for Data Science
This gentle introduction to High Performance Computing (HPC) for Data Science using the Message Passing Interface (MPI) standard has been designed as a first course for undergraduates on parallel programming on distributed memory models, and requires only basic programming notions.Divided into two parts the first part covers high performance computing using C++ with the Message Passing Interface (MPI) standard followed by a second part providing high-performance data analytics on computer clusters.In the first part, the fundamental notions of blocking versus non-blocking point-to-point communications, global communications (like broadcast or scatter) and collaborative computations (reduce), with Amdalh and Gustafson speed-up laws are described before addressing parallel sorting and parallel linear algebra on computer clusters. The common ring, torus and hypercube topologies of clusters are then explained and global communication procedures on these topologies are studied. This first part closes with the MapReduce (MR) model of computation well-suited to processing big data using the MPI framework.In the second part, the book focuses on high-performance data analytics. Flat and hierarchical clustering algorithms are introduced for data exploration along with how to program these algorithms on computer clusters, followed by machine learning classification, and an introduction to graph analytics. This part closes with a concise introduction to data core-sets that let big data problems be amenable to tiny data problems.Exercises are included at the end of each chapter in order for students to practice the concepts learned, and a final section contains an overall exam which allows them to evaluate how well they have assimilated the material covered in the book.
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Introduction to Web Mapping
A web map is an interactive display of geographic information, in the form of a web page, that you can use to tell stories and answer questions. Web maps have numerous advantages over traditional mapping techniques, such as the ability to display up-to-date or even real-time information, easy distribution to end users, and highly customized interactive content. Introduction to Web Mapping teaches you how to develop online interactive web maps and web mapping applications, using standard web technologies: HTML, CSS and JavaScript. The core technologies are introduced in Chapters 1-5, focusing on the specific aspects which are most relevant to web mapping. Chapters 6-13 then implement the material and demonstrate key concepts for building and publishing interactive web maps. The book: Gives an introduction to fundamental web technologies: HTML, CSS and JavaScript Covers Leaflet, the popular open-source JavaScript library for building web maps Describes the GeoJSON vector layer format and the Ajax technique for loading data Shows how spatial database APIs, such as the CARTO platform, can be combined with a web map to query and display large amounts of data Introduces client-side geoprocessing with the Turf.js JavaScript library, for applying spatial operators in the browser Demonstrates a complex web mapping application for collecting crowdsourced data, combining Leaflet, CARTO and the Leaflet.draw plugin Goes over 69 complete code examples and includes 9 solved exercises for building web maps and web pages (downloadable code is provided in the online supplement)The book is intended for beginners with no background in web technologies or programming. Nevertheless, some prior experience with computers and programming is beneficial. The book can be used for self-study, or as a textbook in a standard undergraduate "Web mapping" course in a Geography department, intended for students specializing in Geographic Information Systems (GIS).
R 12,271.30
Introduction to Compilers and Language Design
A compiler translates a program written in a high level language into a program written in a lower level language. For students of computer science, building a compiler from scratch is a rite of passage: a challenging and fun project that offers insight into many different aspects of computer science, some deeply theoretical, and others highly practical. This book offers a one semester introduction into compiler construction, enabling the reader to build a simple compiler that accepts a C-like language and translates it into working X86 or ARM assembly language. It is most suitable for undergraduate students who have some experience programming in C, and have taken courses in data structures and computer architecture.
R 1,342.22
Introduction to Scilab
Familiarize yourself with Scilab using this concise, practical tutorial that is focused on writing code to learn concepts. Starting from the basics, this book covers array-based computing, plotting, and working with files in Scilab. Introduction to Scilab is useful for industry engineers, researchers, and students who are looking for open-source solutions for numerical computation.In this book you will learn by doing, avoiding technical jargon, which makes the concepts easy to learn. First you’ll see how to run basic calculations, absorbing technical complexities incrementally as you progress toward advanced topics. Throughout, the language is kept simple to ensure that readers at all levels can grasp the concepts. After reading this book, you will come away with sample code that can be re-purposed and applied to your own projects using Scilab.What You'll LearnApply sample code to your engineering or science problemsWork with Scilab arrays, functions, and loops Use Scilab’s plotting functions for data visualizationSolve numerical computing and computational engineering problems with ScilabWho This Book Is ForEngineers, scientists, researchers, and students who are new to Scilab. Some prior programming experience would be helpful but not required.
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