A more accessible approach than most competitor texts, which move into advanced, research-level topics too quickly for today's students. Part I is comprehensive in providing all necessary mathematical underpinning, particularly for those who need more opportunity to develop their mathematical competence. More confident students may move directly to Part II and dip back into Part I as a reference. Ideal for use as an introductory text for courses in quantum computing. Fully worked examples illustrate the application of mathematical techniques. Exercises throughout develop concepts and enhance understanding. End-of-chapter exercises offer more practice in developing a secure foundation.

Told over a series of daily journal logs, One-Week Dungeons: Diaries of a Seven-Day Roguelike Challenge chronicles the journeys of eleven 7DRL participants as they race to build their dream games before the clock expires.

Making a great board game and pitching it to publishers are two completely different things. If you've got a game that you want to share with the world but don't know what to do next, this book will help you navigate through exactly what steps to take. You'll discover: How to find the right publisher Exactly what publishers are looking for How to create a sell sheet that will actually sell your game How to negotiate the best deal and get paid more for your game What to look out for in contracts to make sure you don't get exploited You'll learn from Joe's experiences as a full-time board game designer and instructor, along with tips and stories from a dozen other published designers, plus the exact things that publishers want. Direct from 16 established publishers.

Tackles a topic in a concise and accessible way that most believe too advanced to pick up easily. Author has over 40 years teaching and industry experience which they utilize in this book. Contains an appendix with extended code and examples of topics discussed in text.

This new volume provides the information needed to understand the simplex method, the revised simplex method, dual simplex method, and more for solving linear programming problems. Following a logical order, the book first gives a mathematical model of the linear problem programming and describes the usual assumptions under which the problem is solved. It gives a brief description of classic algorithms for solving linear programming problems as well as some theoretical results. It goes on to explain the definitions and solutions of linear programming problems, outlining the simplest geometric methods and showing how they can be implemented. Practical examples are included along the way. The book concludes with a discussion of multi-criteria decision-making methods. Advances in Optimization and Linear Programming is a highly useful guide to linear programming for professors and students in optimization and linear programming.

It explores a variety of modern applications in soft computing, including bioinspired computing, reconfigurable computing, fuzzy logic, fusion-based learning, intelligent healthcare systems, bioinformatics, data mining, functional approximation, genetic and evolutionary algorithms, hybrid models, machine learning, meta heuristics, neuro fuzzy system, and optimization principles. The book acts as a reference book for AI developers, researchers, and academicians as it addresses the recent technological developments in the field of soft computing.

All games are potentially transformative experiences because they engage the player in dynamic action. When repurposed in an educational context, even highly popular casual games played online to pass the time can engage players in a way that deepens learning. Games as Transformative Experiences for Critical Thinking, Cultural Awareness, and Deep Learning: Strategies & Resources examines the learning value of a wide variety of games across multiple disciplines. Organized just like a well-made game, the book is divided into four parts highlighting classroom experiences, community and culture, virtual learning, and interdisciplinary instruction. The author crosses between the high school and college classroom and addresses a range of disciplines, both online and classroom practice, the design of curriculum, and the transformation of assessment practices. In addition to a wealth of practical exercises, resources, and lesson ideas, the book explains how to use a wide and diverse range of games from casual to massively multiplayer online games for self-improvement as well as classroom situations.

Videogames and Agency explores the trend in videogames and their marketing to offer a player higher volumes, or even more distinct kinds, of player freedom. The book offers a new conceptual framework that helps us understand how this freedom to act is discussed by designers, and how that in turn reflects in their design principles. What can we learn from existing theories around agency? How do paratextual materials reflect design intention with regards to what the player can and cannot do in a videogame? How does game design shape the possibility space for player action? Through these questions and selected case studies that include AAA and independent games alike, the book presents a unique approach to studying agency that combines game design, game studies, and game developer discourse. By doing so, the book examines what discourses around player action, as well as a game's design can reveal about the nature of agency and videogame aesthetics. This book will appeal to readers specifically interested in videogames, such as game studies scholars or game designers, but also to media studies students and media and screen studies scholars less familiar with digital games.

Discusses concepts such as Basic Programming Principles, OOP Principles, Database Programming, GUI Programming, Network Programming, Data Analytics and Visualization, Statistical Analysis, Virtual Reality, Web Development, Machine Learning, Deep Learning Provides the code and the output for all the concepts discussed Includes a case study at the end of each chapter

Key Features: This work aims to be the most approachable book about UX. Many books on the topic are highly specialized and are not easy to read for people who just want to understand it better. This book is easy to read and aims to popularize the UX mindset while debunking its main misconceptions. Small format size makes it easy to carry around. Includes content relatable and meaningful to the readers by taking many examples from everyday life with a conversational and light writing style. It tackles the psychology, design, research, process, strategy, and ethics behind offering the best experience with products, systems, or services. Includes a glossary.

This book is designed as a reference book and presents a systematic approach to analyze evolutionary and nature-inspired population-based search algorithms. Beginning with an introduction to optimization methods and algorithms and various enzymes, the book then moves on to provide a unified framework of process optimization for enzymes with various algorithms. The book presents current research on various applications of machine learning and discusses optimization techniques to solve real-life problems. The book compiles the different machine learning models for optimization of process parameters for production of industrially important enzymes. The production and optimization of various enzymes produced by different microorganisms are elaborated in the book It discusses the optimization methods that help minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making Covers the best-performing methods and approaches for optimization sustainable enzymes production with AI integration in a real-time environment Featuring valuable insights, the book helps readers explore new avenues leading towards multidisciplinary research discussions The book is aimed primarily at advanced undergraduates and graduates studying machine learning, data science and industrial biotechnology. Researchers and professionals will also find this book useful.

Quickly learn the most widely used front-end development language with ease and confidence React JS Foundations: Building User Interfaces with ReactJS - An Approachable Guide walks readers through the fundamental concepts of programming with the explosively popular front-end tool known as React JS. Written by an accomplished full-stack engineer, speaker, and community organizer, React JS Foundations teaches readers how to understand React and how to begin building applications with it. The book: Explains and clarifies technical terminology with relevant and modern examples to assist people new to programming understand the language Helps experienced programmers quickly get up to speed with React Is stocked throughout with practical and applicable examples of day-to-day React work Perfect for beginner, intermediate, and advanced programmers alike, React JS Foundations will quickly bring you up to speed on one of the most useful and widely used front-end languages on the web today. You can start building your first application today.

"The first edition of Deep Learning with Python is one of the best books on the subject. The second edition made it even better." - Todd Cook The bestseller revised! Deep Learning with Python, Second Edition is a comprehensive introduction to the field of deep learning using Python and the powerful Keras library. Written by Google AI researcher Francois Chollet, the creator of Keras, this revised edition has been updated with new chapters, new tools, and cutting-edge techniques drawn from the latest research. You'll build your understanding through practical examples and intuitive explanations that make the complexities of deep learning accessible and understandable. about the technology Machine learning has made remarkable progress in recent years. We've gone from near-unusable speech recognition, to near-human accuracy. From machines that couldn't beat a serious Go player, to defeating a world champion. Medical imaging diagnostics, weather forecasting, and natural language question answering have suddenly become tractable problems. Behind this progress is deep learning-a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications across every industry sector about the book Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. You'll learn directly from the creator of Keras, Francois Chollet, building your understanding through intuitive explanations and practical examples. Updated from the original bestseller with over 50% new content, this second edition includes new chapters, cutting-edge innovations, and coverage of the very latest deep learning tools. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects. what's inside Deep learning from first principles Image-classification, imagine segmentation, and object detection Deep learning for natural language processing Timeseries forecasting Neural style transfer, text generation, and image generation about the reader Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required. about the author Francois Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does AI research, with a focus on abstraction and reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others.

Basics of Game Design is for anyone wanting to become a professional game designer. Focusing on creating the game mechanics for data-driven games, it covers role-playing, real-time strategy, first-person shooter, simulation, and other games. Written by a 25-year veteran of the game industry, the guide offers detailed explanations of how to design the data sets used to resolve game play for moving, combat, solving puzzles, interacting with NPCs, managing inventory, and much more. Advice on developing stories for games, building maps and levels, and designing the graphical user interface is also included.

Programming in Scala is the definitive book on Scala, the popular language for the Java platform that blends object-oriented and functional programming concepts into a unique and powerful tool for developers. The fifth edition has been updated to cover new features up to, and including, Scala version 3.0. The Scala language has been exploding in popularity in recent years. More than 54,000 copies of Programming in Scala have been sold since the first edition was published in 2008.

Features Teaches software design by showing programmers how to build the tools they use every day. Each chapter includes exercises to help readers check and deepen their understanding. All the example code can be downloaded, re-used, and modified under an open license.

Revealing the flaws in human decision making, this book explores how AI can be used to optimise decisions for improved business outcomes and efficiency, as well as looking ahead into the significant contributions Decision Intelligence (DI) can make to society and the ethical challenges it may raise. Offering an impressive framework of Decision Intelligence (DI), from the theories and concepts used to design autonomous intelligent agents to the technologies that power DI systems and the ways in which companies use decision-making building blocks to build DI solutions that enable businesses to democratise AI, this book provides a systematic approach to AI intelligence and human involvement. Replete with case studies on DI application, as well as wider discussions on the social implications of the technology, this book appeals to both students of AI and data solutions and businesses considering DI adoption.

Features Focus on the foundational theory underpinning Reinforcement Learning Suitable as a primary text for courses in Reinforcement Learning, but also as supplementary reading for applied/financial mathematics, programming, and other related courses Suitable for a professional audience of quantitative analysts or industry specialists Blends theory/mathematics, programming/algorithms and real-world financial nuances while always striving to maintain simplicity and to build intuitive understanding.

Learning Java Through Games teaches students how to use the different features of the Java language as well as how to program. Suitable for self-study or as part of a two-course introduction to programming, the book covers as much material as possible from the latest Java standard while requiring no previous programming experience. Taking an application-motivated approach, the text presents an abundance of games. Students must read through the whole chapter to understand all the features that are needed to implement the game. Most chapters start with a description of a game and then introduce different Java constructs for implementing the features of the game on need-to-use bases. The text teaches students not only how to write code that works but also how to follow good software practices. All sample programs in the text strive to achieve low cohesion and high coupling-the hallmarks of well-designed code. Many programs are refactored multiple times to achieve code that is easy to understand, reuse, and maintain. The first part of the book covers basic programming techniques, such as conditional statements, loops, methods, arrays, and classes. The second part focuses on more advanced topics, including class inheritance, recursions, sorting algorithms, GUI programming, exception handling, files, and applets.

Explore the fascinating and rich world of Secret Key cryptography! This book provides practical methods for encrypting messages, an interesting and entertaining historical perspective, and an incredible collection of ciphers and codes-including 30 unbreakable methods. In Secret Key Cryptography: Ciphers, from simple to unbreakable you will: Measure the strength of your ciphers and learn how to guarantee their security Construct and incorporate data-compression codes Generate true random numbers in bulk Construct huge primes and safe primes Add an undetectable backdoor to a cipher Defeat hypothetical ultracomputers that could be developed decades from now Construct 30 unbreakable ciphers Secret Key Cryptography gives you a toolbox of cryptographic techniques and Secret Key methods. The book's simple, non-technical language is easy to understand and accessible for any reader, even without the advanced mathematics normally required for cryptography. You'll learn how to create and solve ciphers, as well as how to measure their strength. As you go, you'll explore both historic ciphers and groundbreaking new approaches-including a never-before-seen way to implement the uncrackable One-Time Pad algorithm. about the technology Secret Key cryptography is the backbone of all modern computing infrastructure. Secret Key ciphers use the same key to encrypt and decrypt messages. Properly designed, these algorithms are efficient and practical. Some Secret Key approaches are uncrackable, even under attacks backed by supercomputers or quantum technology! about the book Secret Key Cryptography teaches anyone how to create a wide range of ciphers-even if you have no background in math or creating codes. You'll combine Secret Key techniques to achieve ciphers that are effectively uncrackable and avoid common pitfalls that result in strong-looking but weak ciphers. The book reveals scores of different cipher methods, including both historic examples and current innovations in the field. RETAIL SELLING POINTS * Measure the strength of your ciphers and learn how to guarantee their security * Construct and incorporate data-compression codes * Generate true random numbers in bulk * Construct huge primes and safe primes * Add an undetectable backdoor to a cipher * Defeat hypothetical ultra computers that could be developed decades from now * Construct 30 unbreakable ciphers AUDIENCE For professional engineers, computer scientists, and cryptography hobbyists. No advanced math knowledge is required

Written for developers with some understanding of deep learning algorithms. Experience with reinforcement learning is not required. Grokking Deep Reinforcement Learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal-clear teaching. You'll love the perfectly paced teaching and the clever, engaging writing style as you dig into this awesome exploration of reinforcement learning fundamentals, effective deep learning techniques, and practical applications in this emerging field. We all learn through trial and error. We avoid the things that cause us to experience pain and failure. We embrace and build on the things that give us reward and success. This common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment. * Foundational reinforcement learning concepts and methods * The most popular deep reinforcement learning agents solving high-dimensional environments * Cutting-edge agents that emulate human-like behavior and techniques for artificial general intelligence Deep reinforcement learning is a form of machine learning in which AI agents learn optimal behavior on their own from raw sensory input. The system perceives the environment, interprets the results of its past decisions and uses this information to optimize its behavior for maximum long-term return.

This book is based on deep learning approaches used for the diagnosis of neurological disorders, including basics of deep learning algorithms using diagrams, data tables, and practical examples, for diagnosis of neurodegenerative and neurodevelopmental disorders. It includes application of feed-forward neural networks, deep generative models, convolutional neural networks, graph convolutional networks, and recurrent neural networks in the field of diagnosis of neurological disorders. Along with this, data pre-processing including scaling, correction, trimming, normalization is also included. Offers a detailed description of the deep learning approaches used for the diagnosis of neurological disorders Demonstrates concepts of deep learning algorithms using diagrams, data tables, and examples for the diagnosis of neurodegenerative disorders; neurodevelopmental, and psychiatric disorders. Helps build, train, and deploy different types of deep architectures for diagnosis Explores data pre-processing techniques involved in diagnosis Include real-time case studies and examples This book is aimed at graduate students and researchers in biomedical imaging and machine learning.

Explores the history of telepresence from the 1948 developments of master-slave manipulation, through to current telepresence technology used in space, undersea, surgery and telemedicine, operations in nuclear and other hazardous environments, policing and surveillance, agriculture, construction, mining, warehousing, education, amusement, social media and other contexts Reviews the differing technologies for visual, haptic, tactile remote sensing at the remote site, and the corresponding means of the display to the human operator Reviews the sensing and control technology, its history, and likely future, and discusses the many research and policy issues Reviews psychological experiments in telepresence with relation to virtual and augmented reality Examines social and ethical concerns: ease of spying, mischief, and crime via remote control of an avatar

Most organizations with a web presence build and operate APIs; the doorway for customers to interact with the company's services. Designing, building, and managing these critical programs affect everyone in the organization, from engineers and product owners to C-suite executives. But the real challenge for developers and solution architects is creating an API platform from the ground up. With this practical book, you'll learn strategies for building and testing REST APIs that use API gateways to combine offerings at the microservice level. Authors James Gough, Daniel Bryant, and Matthew Auburn demonstrate how simple additions to this infrastructure can help engineers and organizations migrate to the cloud; and open the opportunity to connect internal services using technologies like a service mesh. Learn API fundamentals and architectural patterns for building an API platform Explore evolving trends such as asynchronous and streaming APIs Help drive your API program by performing an informed architectural role Build and configure key components of an API platform Deploy gateways and service meshes based on case studies Understand core security and vulnerabilities in API architecture Secure data and services using OAuth 2.0, TLS, and web application firewalls