Programming and scripting languages: general Books

Book SynopsisJava is now well-established as one of the world’s major programming languages, used in everything from desktop applications to web-hosted applications, enterprise systems and mobile devices. Java applications cover cloud-based services, the Internet of Things, self-driving cars, animation, game development, big data analysis and many more domains.The second edition of Foundational Java: Key Elements and Practical Programming presents a detailed guide to the core features of Java – and some more recent innovations – enabling the reader to build their skills and confidence though tried-and-trusted stages, supported by exercises that reinforce the key learning points. All the most useful and commonly applied Java syntax and libraries are introduced, along with many example programs that can provide the basis for more substantial applications. Use of the Eclipse Integrated Development Environment (IDE) and the JUnit testing framework is integral to the book, ensuring maximum productivity and code quality when learning Java, although to ensure that skills are not confined to one environment the fundamentals of the Java compiler and run time are also explained. Additionally, coverage of the Ant tool will equip the reader with the skills to automatically build, test and deploy applications independent of an IDE.Topics and features:• Presents the most up-to-date information on Java, including Java 14• Examines the key theme of unit testing, introducing the JUnit 5 testing framework to emphasize the importance of unit testing in modern software development• Describes the Eclipse IDE, the most popular open source Java IDE and explains how Java can be run from the command line• Includes coverage of the Ant build tool• Contains numerous code examples and exercises throughout• Provides downloadable source code, self-test questions, PowerPoint slides and other supplementary material at the website http://www.foundjava.comThis hands-on, classroom-tested textbook/reference is ideal for undergraduate students on introductory and intermediate courses on programming with Java. Professional software developers will also find this an excellent self-study guide/refresher on the topic.Dr. David Parsons is National Postgraduate Director at The Mind Lab, Auckland, New Zealand. He has been teaching programming in both academia and industry since the 1980s and writing about it since the 1990s.Table of ContentsThe Java StoryCompiling and Running Java ProgramsData Types, Arithmetic and ArraysControl StructuresCreating ObjectsCreating Domain ClassesObjects Working Together: Association, Aggregation and CompositionInheritance, Polymorphism and InterfacesException HandlingUnit Testing With JUnitExploring the Java LibrariesThe Collections Framework and GenericsInput and Output StreamsAutomatic Building and Testing with AntJava and the Database (JDBC)MultithreadingBuilding GUIs with the JFC Swing LibraryEvent Driven ProgrammingDialogs and Menus, Models and ViewsJava Web Start and Applets

Read more less

Book SynopsisThis book teaches algebra and geometry. The authors dedicate chapters to the key issues of matrices, linear equations, matrix algorithms, vector spaces, lines, planes, second-order curves, and elliptic curves. The text is supported throughout with problems, and the authors have included source code in Python in the book. The book is suitable for advanced undergraduate and graduate students in computer science. Trade Review“It is most interesting to combine a classical mathematical topic with a new evolving programming language and exactly this is obtained by this book. … This material is used as a case study for their implementation for solving problems in theoretical and practical cryptography. The ‘roadmap’ of the content of this also quite interesting.” (Panayiotis Vlamos, zbMATH 1480.00002, 2022)Table of ContentsMatrices and Matrix Algorithms.- Matrix Algebra.- Systems of Linear Equations.- Complex Numbers and Matrices.- Vector Spaces.- Vectors in a Three-Dimensional Space.- Equation of a Straight Line on a Plane.- Equation of a Plane in Space.- Equation of a Line in Space.- Bilinear and Quadratic Forms.- Curves of the Second-Order.- Elliptic Curves.- Appendix A, Basic Operators in Python and C.- Appendix B, Trigonometric Formulae.- Appendix C, The Greek Alphabet.- References.- Name Index.- Subject Index.

Read more less

Book SynopsisThe main goal of this book is to teach fundamental programming principles to beginners using Julia, one of the fastest growing programming languages today. Julia can be classified as a "modern" language, possessing many features not available in more popular languages like C and Java. The book is organized in 10 chapters. Chapter 1 gives an overview of the programming process. It shows how to write a first Julia program and introduces some of the basic building blocks needed to write programs. Chapter 2 is all about numbers—integers, floating-point, operators, expressions—how to work with them and how to print them. Chapter 3 shows how to write programs which can make decisions. It explains how to use if and if…else statements. Chapter 4 explains the notion of ‘looping’, implemented using for and while statements. It also explains how to read data from a file and write results to a file. Chapter 5 formally treats with functions, enabling a (large) program to be broken up into smaller manageable units which work together to solve a given problem. Chapter 6 is devoted to characters and strings. In Julia, we can work with them as seamlessly as we do with numbers. Chapter 7 tackles array processing, which is significantly easier in Julia than other languages. Chapter 8 is about sorting and searching techniques. Sorting puts data in an order that can be searched more quickly/easily, and makes it more palatable for human consumption. Chapter 9 introduces structures, enabling us to group data in a form that can be manipulated more easily as a unit. Chapter 10 deals with two useful data structures—dictionaries and sets. These enable us to solve certain kinds of problems more easily and conveniently than we can without them. This book is intended for anyone who is learning programming for the first time. The presentation is based on the fact that many students (though not all) have difficulties in learning programming. To overcome this, the book uses an approach which provides clear examples, detailed explanations of very basic concepts and numerous interesting problems (not just artificial exercises whose only purpose is to illustrate some language feature).Table of Contents1. Elementary Concepts.- 2. Numbers.- 3. Selection Logic.- 4. The for and while Statements.- 5. Functions.- 6. Characters & Strings.- 7. Arrays.- 8. Searching, Sorting and Merging.- 9. Structures.- 10. Dictionaries & Sets.

Read more less

Book SynopsisThis textbook assumes very little knowledge of programming so whether you have dabbled with a little JavaScript, played with a bit of Python, written Java or have virtually no programming experience at all you will find that it is for you.The first part of the book introduces Kotlin program structures as well as conditional flow of control features such as if and when expressions as well as iteration loops such as for, while and do-while. Subsequent chapters explain how functions are implemented in Kotlin and introduce concepts from functional programming such as higher order functions and curried functions.The second part focusses on object oriented programming techniques, these include classes, inheritance, abstraction and interfaces. The third part presents container data types such as Arrays, and collections including Lists, Sets and Maps and the fourth part considers concurrency and parallelism using Kotlin coroutines. The book concludes with an introduction to Android mobile application development using Kotlin.Clear steps are provided explaining how to set up your environment and get started writing your own Kotlin programs.An important aspect of the book is teaching by example and there are many examples presented throughout the chapters. These examples are supported by a public GitHub repository that provides complete working code as well as sample solutions to the chapter exercises. This helps illustrate how to write well structured, clear, idiomatic Kotlin to build real applications.Table of ContentsIntroduction.- Part 1: Kotlin Programming.- A First Kotlin Program.- Flow of Control.- Number Guessing Game.- Functions in Kotlin.- Higher Order Functions.- Curried Functions.- Part 2: Object Oriented Kotlin.- Kotlin Classes.- Objects and Companion Objects,- Further Kotlin Properties.- Scope and Conditional Functions.- Class Inheritance.- Abstract Classes.- Interfaces, Delegation and Enumerated Types.- Packages.- Nested and Inner Types.- Data Classes.- Sealed and Inline Classes and Typealias.- Operator Overloading.- Error and Exception Handling.- Extension Functions and Properties.- Part 3: Data Containers.- Arrays.- Collections.- Lists.- Sets.- Maps.- Pairs and Triples.- Generic Types.- Functional Programming and Containers.- Part 4: Concurrent Kotlin.- Coroutines.- Coroutine Channel Communications.- Part 5: Android Development.- Android Overview.- Applications and Activities.- Android Layouts and Events.- Android Tic Tac Toe.

Read more less

Book SynopsisThis book is about the harmonious synthesis of functional programming and numerical computation. It shows how the expressiveness of OCaml allows for fast and safe development of data science applications. Step by step, the authors build up to use cases drawn from many areas of Data Science, Machine Learning, and AI, and then delve into how to deploy at scale, using parallel, distributed, and accelerated frameworks to gain all the advantages of cloud computing environments.To this end, the book is divided into three parts, each focusing on a different area. Part I begins by introducing how basic numerical techniques are performed in OCaml, including classical mathematical topics (interpolation and quadrature), statistics, and linear algebra. It moves on from using only scalar values to multi-dimensional arrays, introducing the tensor and Ndarray, core data types in any numerical computing system. It concludes with two more classical numerical computing topics, the solution of Ordinary Differential Equations (ODEs) and Signal Processing, as well as introducing the visualization module we use throughout this book. Part II is dedicated to advanced optimization techniques that are core to most current popular data science fields. We do not focus only on applications but also on the basic building blocks, starting with Algorithmic Differentiation, the most crucial building block that in turn enables Deep Neural Networks. We follow this with chapters on Optimization and Regression, also used in building Deep Neural Networks. We then introduce Deep Neural Networks as well as topic modelling in Natural Language Processing (NLP), two advanced and currently very active fields in both industry and academia. Part III collects a range of case studies demonstrating how you can build a complete numerical application quickly from scratch using Owl. The cases presented include computer vision and recommender systems. This book aims at anyone with a basic knowledge of functional programming and a desire to explore the world of scientific computing, whether to generally explore the field in the round, to build applications for particular topics, or to deep-dive into how numerical systems are constructed. It does not assume strict ordering in reading – readers can simply jump to the topic that interests them most. Table of ContentsPart I: Numerical Techniques.- 1. Introduction.- 2. Numerical Algorithms.- 3. Statistics.- 4. Linear Algebra.- 5. N-Dimensional Arrays.- 6. Ordinary Differential Equations.- 7. Signal Processing.- Part II: Advanced Data Analysis Techniques.- 8. Algorithmic Differentiation.- 9. Optimisation.- 10. Regression.- 11. Neural Network.- 12. Vector Space Modelling.- Part III: Use Cases.- 13. Case Study: Image Recognition.- 14. Case Study: Instance Segmentation.- 15. Case Study: Neural Style Transfer.- 16. Case Study: Recommender System.

Read more less

Book Synopsis.-  Ghost Swarms: Learning Swarm Rules from Environmental Changes Alone..- A Systematic Evaluation of Evolving Highly Nonlinear BooleanFunctions in Odd Sizes..- Exploring the Impact of Data Scale on Mutation Step Size in SLIM-GSGP..- Multi-Objective Evolutionary Design of Explainable EEG Classifier..- On the Effectiveness of Crossover Operators in Cartesian GeneticProgramming..- Population Diversity, Information Theory and Genetic Improvement..- Introducing Crossover in SLIM-GSGP..- Exploring the Integration of Cellular Structures in GeneticProgramming-based Methods..- Ant-based Metaheuristics Struggle to Solve the Cartesian GeneticProgramming Learning Task..- Designing Lookahead Relocation Rules for the Container RelocationProblem with Genetic Programming..- Evolved and Transparent Pipelines for Biomedical Image Classification..- Unified Piecewise Symbolic Regression..- Was Tournament Selection All We Ever Needed? A Critical Reflectionon Lexicase Selection..- The Role of Stepping Stones in MAP-Elites: Insights from SearchTrajectory Networks..- Micro-Step Time-Series Regression: Insights from System IdentificationUsing Symbolic Regression.

Read more less

Book Synopsis

Read more less

Book SynopsisThis volume, the third of a series, consists of applications of Mathematica® to a potpourri of more advanced topics. These include differential geometry of curves and surfaces, differential equations and special functions and complex analysis. Some of the newest features of Mathematica® are demonstrated and explained and some problems with the current implementation pointed out and possible future improvements suggested. Contains a large number of worked out examples. Explains some of the most recent mathematical features of Mathematica®. Considers topics discussed rarely or not at all in the context of Mathematica®. Can be used to supplement several different courses. Based on actual university courses.

Read more less

Book SynopsisIntroduces students to appropriate use of computer programming within the scientific disciplines using Python. Discusses several common applications of programming and implementation using real world examples and hands on programming exercises. Students learn how to model situations such as image recognition, medical diagnosis, spread of disease, and others. The text could be used by students and lecturers for courses in Python, Numerical Methods, or as a first course in Data Science.

Read more less