This new edition of Introducing Delphi programming: Theory through practice covers the basics of Delphi and includes features of Delphi 6,7 and 8. The book has been written for students taking first year course in Information Systems at universities and Institutes of Technology and is ideal for the independent, distance learner. It teaches students both the practical side of programming and important programming theory.Delphi is a versatile and sophisticated visual programming environment for rapid application development that allows the programmer to develop Windows and Linux programs easily and speedily. Introducing Delphi Programming: Theory through Practice is considered to be the leading introductory text on computer programming. It allows students to gain confidence as they develop their skills in an interesting and practical way.

The ability to clearly specify each step to create a problem-free computer program is a primary skill needed by programmers. Basic Programming Principles 2nd edition guides beginner programmers through the challenges of planning a computer program by presenting the text in a simple and straightforward manner. It contains many examples and exercises with explanations and answers that promote learners' understanding. New exercises provide opportunities for students to apply the principles of programming and problem-solving and learning outcomes highlight the key learning areas. It is an update of Basic Programming Principles: Using Visual Basic.Net 2nd edition without reference to the Visual Basic.Net.

This powerful new book introduces cross-platform app design as an excellent starting point for mastering app development. The book contains numerous applications that you can adapt to different projects. You can use this book for independent study or for your project courses. The book introduces HTML5, CSS3, JavaScript, jQuery Mobile, Node.js, JSON, localStorage, sessionStorage, NoSQL using MongoDB, SQL using MySQL, templating using handlebars, and maps. A strong app-centric view emphasizes appropriate subsets of these technologies to help you develop non-trivial apps. While apps continue to evolve and change, the technologies presented form the backbone of future cross-platform app development. You will learn to work with all major mobile and web platforms using the book's active learning approach that has you typing code in parallel as the apps are developed. Exercises further encourage you to make changes to the code and evaluate resulting app behavior.

Event structures are central in Linguistics and Artificial Intelligence research: people can easily refer to changes in the world, identify their participants, distinguish relevant information, and have expectations of what can happen next. Part of this process is based on mechanisms similar to narratives, which are at the heart of information sharing. But it remains difficult to automatically detect events or automatically construct stories from such event representations. This book explores how to handle today's massive news streams and provides multidimensional, multimodal, and distributed approaches, like automated deep learning, to capture events and narrative structures involved in a 'story'. This overview of the current state-of-the-art on event extraction, temporal and casual relations, and storyline extraction aims to establish a new multidisciplinary research community with a common terminology and research agenda. Graduate students and researchers in natural language processing, computational linguistics, and media studies will benefit from this book.

Learning to program isn't just learning the details of a programming language: to become a good programmer you have to become expert at debugging, testing, writing clear code and generally unsticking yourself when you get stuck, while to do well in a programming course you have to learn to score highly in coursework and exams. Featuring tips, stories and explanations of key terms, this book teaches these skills explicitly. Examples in Python, Java and Haskell are included, helping you to gain transferable programming skills whichever language you are learning. Intended for students in Higher or Further Education studying early programming courses, it will help you succeed in, and get the most out of, your course, and support you in developing the software engineering habits that lead to good programs.

Strengthen your competitive advantage with a flawless corporate strategy

"How to Plan and Execute Strategy provides" you with 24 practical steps for creating, implementing, and managing market-defining, growth-driving strategies. Encompassing every stage of the strategic process, this tactic-filled handbook shares exactly what you need to know in order to: Define your businesses Know your market Understand your opportunities and threats Set feasible goals and objectives Create the strategies to achieve your objectives Identify and set priorities Write your business plan Get the right people Communicate the strategy and obtain commitment Integrate across functions Execute with discipline Monitor results, evaluate, and react

Every successful company has benefited from an excellent corporate strategy. With the proven techniques in this portable, hands-on guide, your business will reap the same rewards. How to Plan and Execute Strategy shows how to get a leg up on your competition and sustain your lead for the long run.

Boost Your Productivity - and Your Career -- With a Simple, Smart Time-Management System

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Getting Organized at Work helps you move past the clutter to enjoy unprecedented efficiency and productivity. With two-dozen easy-to-implement, time-saving tactics, this practical guide shows how to uncover and eliminate those nonessential activities that bog you down throughout the day, enabling you to accomplish the maximum amount of work in a minimal amount of time.

"Getting Organized at Work" teaches you how to: Take control of your day o Plan your work o Organize your day Set realistic goals o End the procrastination Prioritize requests o Give specific direction Manage your email o Master incoming calls Plan meetings wisely Delegate for maximum efficiency o Conquer your desk Limit interruptions Add closure to your day o Find more time for yourself

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.

The data structure is a set of specially organized data elements and functions, which are defined to store, retrieve, remove and search for individual data elements. Data Structures using C: A Practical Approach for Beginners covers all issues related to the amount of storage needed, the amount of time required to process the data, data representation of the primary memory and operations carried out with such data. Data Structures using C: A Practical Approach for Beginners book will help students learn data structure and algorithms in a focused way. Resolves linear and nonlinear data structures in C language using the algorithm, diagrammatically and its time and space complexity analysis Covers interview questions and MCQs on all topics of campus readiness Identifies possible solutions to each problem Includes real-life and computational applications of linear and nonlinear data structures This book is primarily aimed at undergraduates and graduates of computer science and information technology. Students of all engineering disciplines will also find this book useful.

For new software engineers, knowing how to programme is only half the battle, and many of the skills and processes key to success are not taught in any school or bootcamp. The Missing README fills in that gap with workplace lessons, best practices, and engineering fundamentals that the authors have taught rookie developers at top companies for more than a decade. This is the book your tech lead wishes every new engineer would read before they start. By the end, you'll know what it takes to transition into the workplace - from CS classes or bootcamps to professional software engineering.

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.

Jump-start your career as a data scientist--learn to develop datasets for exploration, analysis, and machine learning SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis is a resource that's dedicated to the Structured Query Language (SQL) and dataset design skills that data scientists use most. Aspiring data scientists will learn how to how to construct datasets for exploration, analysis, and machine learning. You can also discover how to approach query design and develop SQL code to extract data insights while avoiding common pitfalls. You may be one of many people who are entering the field of Data Science from a range of professions and educational backgrounds, such as business analytics, social science, physics, economics, and computer science. Like many of them, you may have conducted analyses using spreadsheets as data sources, but never retrieved and engineered datasets from a relational database using SQL, which is a programming language designed for managing databases and extracting data. This guide for data scientists differs from other instructional guides on the subject. It doesn't cover SQL broadly. Instead, you'll learn the subset of SQL skills that data analysts and data scientists use frequently. You'll also gain practical advice and direction on how to think about constructing your dataset. Gain an understanding of relational database structure, query design, and SQL syntax Develop queries to construct datasets for use in applications like interactive reports and machine learning algorithms Review strategies and approaches so you can design analytical datasets Practice your techniques with the provided database and SQL code In this book, author Renee Teate shares knowledge gained during a 15-year career working with data, in roles ranging from database developer to data analyst to data scientist. She guides you through SQL code and dataset design concepts from an industry practitioner's perspective, moving your data scientist career forward!

Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Essential Skills--Made Easy!Learn to program in AppleScript, the versatile scripting language built right into Mac OS X and supported by most major applications. AppleScript: A Beginner's Guide shows you how to write powerful scripts with the AppleScript Editor to automate tasks, save time and effort, and automatically generate documents, spreadsheets, and e-mail messages. Debugging and error handling are also covered in this fast-paced tutorial. Designed for Easy Learning Key Skills & Concepts--Chapter-opening lists of specific skills covered in the chapter Ask the Expert--Q&A sections filled with bonus information and helpful tips Try This--Hands-on exercises that show you how to apply your skills Notes--Extra information related to the topic being covered Tips--Helpful reminders or alternative ways of doing things Cautions--Errors and pitfalls to avoid Annotated Syntax--Example code with commentary that describes the programming techniques being illustrated Ready-to-use code at www.mhprofessional.com/computingdownload Guy Hart-Davis is the author of Mac OS X Leopard QuickSteps, How to Do Everything iPod, iPhone, & iTunes, Fifth Edition, HTML, XHTML & CSS QuickSteps, and several other computer books.

A fully updated tutorial on the basics of the Python programming language for science students Python is a computer programming language that has gained popularity throughout the sciences. This fully updated second edition of A Student's Guide to Python for Physical Modeling aims to help you, the student, teach yourself enough of the Python programming language to get started with physical modeling. You will learn how to install an open-source Python programming environment and use it to accomplish many common scientific computing tasks: importing, exporting, and visualizing data; numerical analysis; and simulation. No prior programming experience is assumed. This guide introduces a wide range of useful tools, including: Basic Python programming and scripting Numerical arrays Two- and three-dimensional graphics Animation Monte Carlo simulations Numerical methods, including solving ordinary differential equations Image processing Numerous code samples and exercises-with solutions-illustrate new ideas as they are introduced. This guide also includes supplemental online resources: code samples, data sets, tutorials, and more. This edition includes new material on symbolic calculations with SymPy, an introduction to Python libraries for data science and machine learning (pandas and sklearn), and a primer on Python classes and object-oriented programming. A new appendix also introduces command line tools and version control with Git.

NVIDIA's Full-Color Guide to Deep Learning: All You Need to Get Started and Get Results "To enable everyone to be part of this historic revolution requires the democratization of AI knowledge and resources. This book is timely and relevant towards accomplishing these lofty goals." -- From the foreword by Dr. Anima Anandkumar, Bren Professor, Caltech, and Director of ML Research, NVIDIA "Ekman uses a learning technique that in our experience has proven pivotal to success-asking the reader to think about using DL techniques in practice. His straightforward approach is refreshing, and he permits the reader to dream, just a bit, about where DL may yet take us." -- From the foreword by Dr. Craig Clawson, Director, NVIDIA Deep Learning Institute Deep learning (DL) is a key component of today's exciting advances in machine learning and artificial intelligence. Learning Deep Learning is a complete guide to DL. Illuminating both the core concepts and the hands-on programming techniques needed to succeed, this book is ideal for developers, data scientists, analysts, and others--including those with no prior machine learning or statistics experience. After introducing the essential building blocks of deep neural networks, such as artificial neurons and fully connected, convolutional, and recurrent layers, Magnus Ekman shows how to use them to build advanced architectures, including the Transformer. He describes how these concepts are used to build modern networks for computer vision and natural language processing (NLP), including Mask R-CNN, GPT, and BERT. And he explains how a natural language translator and a system generating natural language descriptions of images. Throughout, Ekman provides concise, well-annotated code examples using TensorFlow with Keras. Corresponding PyTorch examples are provided online, and the book thereby covers the two dominating Python libraries for DL used in industry and academia. He concludes with an introduction to neural architecture search (NAS), exploring important ethical issues and providing resources for further learning. Explore and master core concepts: perceptrons, gradient-based learning, sigmoid neurons, and back propagation See how DL frameworks make it easier to develop more complicated and useful neural networks Discover how convolutional neural networks (CNNs) revolutionize image classification and analysis Apply recurrent neural networks (RNNs) and long short-term memory (LSTM) to text and other variable-length sequences Master NLP with sequence-to-sequence networks and the Transformer architecture Build applications for natural language translation and image captioning NVIDIA's invention of the GPU sparked the PC gaming market. The company's pioneering work in accelerated computing--a supercharged form of computing at the intersection of computer graphics, high-performance computing, and AI--is reshaping trillion-dollar industries, such as transportation, healthcare, and manufacturing, and fueling the growth of many others. Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

Nowadays, finance, mathematics, and programming are intrinsically linked. This book provides the relevant foundations of each discipline to give you the major tools you need to get started in the world of computational finance. Using an approach where mathematical concepts provide the common background against which financial ideas and programming techniques are learned, this practical guide teaches you the basics of financial economics. Written by the best-selling author of Python for Finance, Yves Hilpisch, Financial Theory with Python explains financial, mathematical, and Python programming concepts in an integrative manner so that the interdisciplinary concepts reinforce each other. Draw upon mathematics to learn the foundations of financial theory and Python programming Learn about financial theory, financial data modeling, and the use of Python for computational finance Leverage simple economic models to better understand basic notions of finance and Python programming concepts Use both static and dynamic financial modeling to address fundamental problems in finance, such as pricing, decision-making, equilibrium, and asset allocation Learn the basics of Python packages useful for financial modeling, such as NumPy, pandas, Matplotlib, and SymPy

Systems programming provides the foundation for the world's computation. Developing performance-sensitive code requires a programming language that puts programmers in control of how memory, processor time, and other system resources are used. The Rust systems programming language combines that control with a modern type system that catches broad classes of common mistakes, from memory management errors to interthread data races. With this practical guide, experienced systems programmers will learn how to successfully bridge the gap between performance and safety using Rust. Jim Blandy, Jason Orendorff, and Leonora Tindall demonstrate how Rust's features put programmers in control over memory consumption and processor use by combining predictable performance with memory safety and trustworthy concurrency. You'll learn: Rust's fundamental data types and the core concepts of ownership and borrowing Language basics including error handling, crates and modules, structs, and enums How to write flexible, efficient code with traits and generics Rust's key power tools: closures, iterators, and asynchronous programming Collections, strings and text, input and output, concurrency, macros, unsafe code, and interfacing with foreign functions This updated edition covers Rust 1.50 (February 2021).

Make your good Python code even better by following proven and effective pythonic programming tips. Avoid logical errors that usually go undetected by Python linters and code formatters, such as frequent data look-ups in long lists, improper use of local and global variables, and mishandled user input. Discover rare language features, like rational numbers, set comprehensions, counters, and pickling, that may boost your productivity. Discover how to apply general programming patterns, including caching, in your Python code. Become a better-than-average Python programmer, and develop self-documented, maintainable, easy-to-understand programs that are fast to run and hard to break. Python is one of the most popular and rapidly growing modern programming languages. With more than 200 standard libraries and even more third-party libraries, it reaches into the software development areas as diverse as artificial intelligence, bioinformatics, natural language processing, and computer vision. Find out how to improve your understanding of the spirit of the language by using one hundred pythonic tips to make your code safer, faster, and better documented. This programming style manual is a quick reference of helpful hints and a random source of inspiration. Choose the suitable data structures for searching and sorting jobs and become aware of how a wrong choice may cause your application to be completely ineffective. Understand global and local variables, class and instance attributes, and information-hiding techniques. Create functions with flexible interfaces. Manage intermediate computation results by caching them in files and memory to improve performance and reliability. Polish your documentation skills to make your code easy for other programmers to understand. As a bonus, discover Easter eggs cleverly planted in the standard library by its developers. Polish, secure, and speed-up your Python applications, and make them easier to maintain by following pythonic programming tips. What You Need: You will need a Python interpreter (ideally, version 3.4 or above) and the standard Python library that usually comes with the interpreter.

Haskell is a purely functional language that allows programmers to rapidly develop clear, concise, and correct software. The language has grown in popularity in recent years, both in teaching and in industry. This book is based on the author's experience of teaching Haskell for more than twenty years. All concepts are explained from first principles and no programming experience is required, making this book accessible to a broad spectrum of readers. While Part I focuses on basic concepts, Part II introduces the reader to more advanced topics. This new edition has been extensively updated and expanded to include recent and more advanced features of Haskell, new examples and exercises, selected solutions, and freely downloadable lecture slides and example code. The presentation is clean and simple, while also being fully compliant with the latest version of the language, including recent changes concerning applicative, monadic, foldable, and traversable types.

Quickly learn the ropes with the Rust programming language using this practical, step-by-step guide In Beginning Rust Programming, accomplished programmer and author Ric Messier delivers a highly practical, real-world guide to coding with Rust. Avoiding dry, theoretical content and "Hello, world"-type tutorials of questionable utility, the book dives immediately into functional Rust programming that takes advantage of the language's blazing speed and memory efficiency. Designed from the ground up to give you a running start to using the multiparadigm system programming language, this book will teach you to: Solve real-world computer science problems of practical importance Use Rust's rich type system and ownership model to guarantee memory-safety and thread-safety Integrate Rust with other programming languages and use it for embedded devices Perfect for programmers with some experience in other languages, like C or C++, Beginning Rust Programming is also a great pick for students new to programming and seeking a user-friendly and robust language with which to start their coding career.

NOTE: After the release of the Developer Complete Study Guide, Oracle completely revamped the Java SE 11 certification by retiring Exams 1Z0-815 and 1Z0-816. You're now only required to pass the new Exam 1Z0-819. The Upgrade Exam 1Z0-817 remains the same. Even though the exams have changed, the same topics are covered (but are presented in a different order). You can rest assured, however, that this Certification Kit provides complete coverage of the Java SE 11 certification exam. NEW Certification Kit focuses on 100% of the objectives for the new exam! The Certification Kit incude two books: OCP Oracle Certified Professional Java SE 11 Developer Complete Study Guide: Exam 1Z0-815, Exam 1Z0-816, and Exam 1Z0-817 is designed to make you fully prepared to understand the job role and to take the exams. In particular, developers will need to learn functional programming for the first time to pass the certification. This comprehensive study guide covers all of the key topic areas Java programmers will need to be familiar with.OCP Oracle Certified Professional Java SE 11 Developer Practice Tests: Exam 1Z0-819 and Upgrade Exam 1Z0-817 is organized in two parts, this book provides 28 chapter tests, covering all the OCP Java SE 11 Programmer I and Prorammer II objective domains. PLUS it offers two additional practice exams, for a total of over a 1000 practice test questions. This book helps you gain the confidence you need for taking the OCP Java SE 11 Programmer I and Programmer II exams. With this Certification Kit, Java developers will gain the information, understanding, and practice they need to pass the OCP Java SE 11 Developer exam as well as the upgrade exam. Readers will also have access to Sybex's superior online interactive learning environment and test bank, including an assessment test, chapter tests, bonus practice exam questions, electronic flashcards, and a searchable Glossary of the most important terms readers will need to understand.

The widespread adoption of AI and machine learning is revolutionizing many industries today. Once these technologies are combined with the programmatic availability of historical and real-time financial data, the financial industry will also change fundamentally. With this practical book, you'll learn how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading. Author Yves Hilpisch shows practitioners, students, and academics in both finance and data science practical ways to apply machine learning and deep learning algorithms to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book. In five parts, this guide helps you: Learn central notions and algorithms from AI, including recent breakthroughs on the way to artificial general intelligence (AGI) and superintelligence (SI) Understand why data-driven finance, AI, and machine learning will have a lasting impact on financial theory and practice Apply neural networks and reinforcement learning to discover statistical inefficiencies in financial markets Identify and exploit economic inefficiencies through backtesting and algorithmic trading--the automated execution of trading strategies Understand how AI will influence the competitive dynamics in the financial industry and what the potential emergence of a financial singularity might bring about

Design and develop sophisticated 2D games that are as much fun to make as they are to play. From particle effects and pathfinding to social integration and monetization, this complete tour of Apple's powerful suite of game technologies covers it all. Familiar with Swift but new to game development? No problem. Start with the basics and then layer in the complexity as you work your way through three exciting - and fully playable - games. In the end, you'll know everything you need to go off and create your own video game masterpiece for any Apple platform. Discover the power of Apple Game Frameworks, Xcode, and Swift by building three exciting games: Gloop Drop - a new twist on a classic arcade game, Val's Revenge - a roguelike dungeon crawler, and Hog - a social player vs. player mobile dice game. With Apple Game Frameworks, you can create high-performance, power-efficient games that work across all Apple platforms, including iOS, macOS, tvOS, and watchOS. In this book, you'll discover how to... Design and develop rich 2D gaming experiences using Apple's built-in game frameworks. Harness the power of SpriteKit using Xcode and Swift to create engaging player experiences. Use the visual Scene Editor to build complete scenes. Unleash the power of the Particle Editor to create amazing effects. Use GameplayKit to add advanced features to your games like pathfinding, artificial intelligence, and complex rule systems. Build larger, more complex worlds with tile maps and Xcode's visual Tile Map editor. Bring people together using GameKit and Game Center, Apple's social gaming network. Increase revenue with third-party banner ads and rewarded ads using Google AdMob (TM). Monetize your games with StoreKit and in-app purchases. So, grab your gear and get your game on - it's time to level up your skills. What You Need: macOS Mojave 10.14.6 or newer Xcode 11.3 or newer Basic knowledge of Swift 5.1.4 or newer