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.

The aim of this book is to provide detailed coverage of the topics in the new OCR AS and A Level Computer Science specifications H046 / H446. The book is divided into twelve sections and within each section, each chapter covers material that can comfortably be taught in one or two lessons. Material that is applicable only to the second year of the full A Level is clearly marked. Sometimes this may include an entire chapter and at other times, just a small part of a chapter. Each chapter contains exercises and questions, some new and some from past examination questions. Answers to all these are available to teachers only in a free Teacher's Pack which can be ordered from our website www.pgonline.co.uk. This book has been written to cover the topics which will be examined in the written papers at both AS and A Level. Sections 10, 11 and 12 relate principally to problem solving skills, with programming techniques covered in sufficient depth to allow students to answer questions in Component 02. Pseudocode, rather than any specific programming language, is used in the algorithms given in the text. Sample Python programs which implement many of the algorithms are included in a folder with the Teacher's Pack.

The book is concerned with contemporary methodologies used for automatic text summarization. It proposes interesting approaches to solve well-known problems on text-summarization using computational intelligence (CI) techniques including cognitive approaches. A better understanding of the cognitive basis of the summarization task is still an open research issue, an extent of its use in text summarization is highlighted for further exploration. With the ever-growing text and people on research has little time to spare for extensive reading, where, summarized information helps for a better understanding of the context at a shorter time. This book helps students and researchers to automatically summarize the text documents in an efficient and effective way. The computational approaches and the research techniques presented guides to achieve text summarization at ease. The summarized text generated supports readers to learn the context or the domain at a quicker pace. The book is presented with reasonable amount of illustrations and examples convenient for the readers to understand and implement for their use. The book is not to make readers understand what text summarization is, but for people to perform text summarization using various approaches. This also describes measures that can help to evaluate, determine and explore the best possibilities for text summarization to analyse and use for any specific purpose. The illustration is based on social media and healthcare domain, which shows the possibilities to work with any domain for summarization. The new approach for text summarization based on cognitive intelligence is presented for further exploration in the field.

This study, written in the context of its first publication in 1970, discusses and documents the invasion of privacy by the corporation and the social institution in the search for efficiency in information processing. Discussing areas such as the impact of the computer on administration, privacy and the storage on information, the authors assess the technical and social feasibility of constructing integrated data banks to cover the details of populations. The book was hugely influential both in terms of scholarship and legislation, and the years following saw the introduction of the Data Protection Act of 1984, which was then consolidated by the Act of 1998. The topics under discussion remain of great concern to the public in our increasingly web-based world, ensuring the continued relevance of this title to academics and students with an interest in data protection and public privacy.

Blockchain technology has been penetrating every aspect of Information and Communications Technology (ICT), and its use has been growing rapidly in recent years. The interest and development of this technology has primarily been driven by the enormous value growth of cryptocurrencies and large investments of venture capital in blockchain start-ups. Blockchain for Smart Systems: Computing Technologies and Applications is intended to clarify and define, in simple terms, the technology behind blockchain. It provides a deep dive into the core fundamentals of blockchain: hashing algorithm behind each block, distributed technology, smart contracts, and private vs. public blockchain. Features Discusses fundamental theories of practical and sophisticated applications of blockchain technology Includes case studies Discusses the concepts with illustrations, appropriate figures, tables, and simple language This book is primarily aimed at undergraduates, graduates, research scholars, academicians, and industry and technology enthusiasts working in various aspects of blockchain technology.

Deep learning is an artificially intelligent entity that teaches itself and can be utilized to make predictions. Deep learning mimics the human brain and provides learned solutions addressing many challenging problems in the area of visual computing. From object recognition to image classification for diagnostics, deep learning has shown the power of artificial deep neural networks in solving real world visual computing problems with super-human accuracy. The introduction of deep learning into the field of visual computing has meant to be the death of most of the traditional image processing and computer vision techniques. Today, deep learning is considered to be the most powerful, accurate, efficient and effective method with the potential to solve many of the most challenging problems in visual computing. This book provides an insight into deep machine learning and the challenges in visual computing to tackle the novel method of machine learning. It introduces readers to the world of deep neural network architectures with easy-to-understand explanations. From face recognition to image classification for diagnosis of cancer, the book provides unique examples of solved problems in applied visual computing using deep learning. Interested and enthusiastic readers of modern machine learning methods will find this book easy to follow. They will find it a handy guide for designing and implementing their own projects in the field of visual computing.

Articulates a series of scientific and technological developments described in a didactic way Shows a broad view of biometrics in several contexts: Current cases of study in five different areas Provides experimental results in different environments (availability of data and computer code to reproduce the experiments) Includes transdisciplinary approaches and discussions for each chapter Innovation as part of the final cases of study: developments are already affecting the new businesses of the digital age and the era of the brain

Double Sequence Spaces and Four-Dimensional Matrices provides readers with a clear introduction to the spaces of double sequences and series, as well as their properties. The book then goes beyond this to investigate paranormed double sequence spaces and their algebraic and topological properties, triangle matrices and their domains in certain spaces of double sequences, dual spaces of double sequence spaces, and matrix transformations between double sequence spaces and related topics. Each chapter contains a conclusion section highlighting the importance of results and pointing out possible new ideas that can be studied further. Features Suitable for students at graduate or post-graduate level and researchers Investigates different types of summable spaces and computes their duals Characterizes several four-dimensional matrix classes transforming one summable space into other Discusses several algebraic and topological properties of new sequence spaces generated by the domain of triangles.

Computational intelligence (CI) in concrete technology has not yet been fully explored worldwide because of some limitations in data sets. This book discusses the selection and separation of data sets, performance evaluation parameters for different types of concrete and related materials, and sensitivity analysis related to various CI techniques. Fundamental concepts and essential analysis for CI techniques such as artificial neural network, fuzzy system, support vector machine, and how they work together for resolving real-life problems, are explained. Features: It is the first book on this fast-growing research field. It discusses the use of various computation intelligence techniques in concrete technology applications. It explains the effectiveness of the methods used and the wide range of available techniques. It integrates a wide range of disciplines from civil engineering, construction technology, and concrete technology to computation intelligence, soft computing, data science, computer science, and so on. It brings together the experiences of contributors from around the world who are doing research in this field and explores the different aspects of their research. The technical content included is beneficial for researchers as well as practicing engineers in the concrete and construction industry.

Since the invention of computers or machines, scientists and researchers are trying very hard to enhance their capabilities to perform various tasks. As a consequence, the capabilities of computers are growing exponentially day by day in terms of diverse working domains, versatile jobs, processing speed, and reduced size. Now, we are in the race to make the computers or machines as intelligent as human beings. Artificial Intelligence (AI) came up as a way of making a computer or computer software think in the similar manner the intelligent humans think. AI is inspired by the study of human brain like how humans think, learn, decide and act while trying to solve a problem. The outcomes of this study are the basis of developing intelligent software and systems or Intelligent Computing (IC). An IC system has the capability of reasoning, learning, problem solving, perception, and linguistic intelligence. The IC systems consist of AI techniques as well as other emerging techniques that make a system intelligent. The use of intelligent computing has been seen in almost every sub-domain of computer science such as networking, software engineering, gaming, natural language processing, computer vision, image processing, data science, robotics, expert systems, and security. Now a days, the use of IC can also be seen for solving various complex problems in diverse domains such as for predicting disease in medical science, predicting land fertility or crop productivity in agriculture science, predicting market growth in economics, weather forecasting and so on. For all these reasons, this book presents the advances in AI techniques, under the umbrella of IC. In this context, the book includes the recent research works have been done in the areas of machine learning, neural networks, deep learning, evolutionary algorithms, genetic algorithms, swarm intelligence, fuzzy systems and so on. This book provides theoretical, algorithmic, simulation, and implementation-based recent research advancements related to the Intelligent Computing.

This book explores how to use generative adversarial networks in a variety of applications and emphasises their substantial advancements over traditional generative models. This book's major goal is to concentrate on cutting-edge research in deep learning and generative adversarial networks, which includes creating new tools and methods for processing text, images, and audio. A Generative Adversarial Network (GAN) is a class of machine learning framework and is the next emerging network in deep learning applications. Generative Adversarial Networks(GANs) have the feasibility to build improved models, as they can generate the sample data as per application requirements. There are various applications of GAN in science and technology, including computer vision, security, multimedia and advertisements, image generation, image translation,text-to-images synthesis, video synthesis, generating high-resolution images, drug discovery, etc. Features: Presents a comprehensive guide on how to use GAN for images and videos. Includes case studies of Underwater Image Enhancement Using Generative Adversarial Network, Intrusion detection using GAN Highlights the inclusion of gaming effects using deep learning methods Examines the significant technological advancements in GAN and its real-world application. Discusses as GAN challenges and optimal solutions The book addresses scientific aspects for a wider audience such as junior and senior engineering, undergraduate and postgraduate students, researchers, and anyone interested in the trends development and opportunities in GAN and Deep Learning. The material in the book can serve as a reference in libraries, accreditation agencies, government agencies, and especially the academic institution of higher education intending to launch or reform their engineering curriculum

Managers in organisations must make rational decisions. Rational decision making is the opposite of intuitive decision making. It is a strict procedure utilising objective knowledge and logic. It involves identifying the problem to solve, gathering facts, identifying options and outcomes, analysing them, considering all the relationships and selecting the decision. Rational decision making requires support: methods and software tools. The identification of the problem to solve needs methods that would measure and evaluate the current situation. Identification and evaluation of options and analysis of the available possibilities involves analysis and optimisation methods. Incorporating intuition into rational decision making needs adequate methods that would translate ideas or observed behaviours into hard data. Communication, observation and opinions recording is hardly possible today without adequate software. Information and data that form the input, intermediate variables and the output must be stored, managed and made accessible in a user-friendly manner. Rational Decisions in Organisations: Theoretical and Practical Aspects presents selected recent developments in the support of the widely understood rational decision making in organisations, illustrated through case studies. The book shows not only the variety of perspectives involved in decision making, but also the variety of domains where rational decision support systems are needed. The case studies present decision making by medical doctors, students and managers of various universities, IT project teams, construction companies, banks and small and large manufacturing companies. Covering the richness of relationships in which the decisions should and must be taken, the book illustrates how modern organisations operate in chains and networks; they have multiple responsibilities, including social, legal, business and ethical duties. Nowadays, managers in organisations can make transparent decisions and consider a multitude of stakeholders and their diverse features, incorporating diverse criteria, using multiple types and drivers of information and decision-making patterns, and referring to numerous lessons learned. As the book makes clear, the marriage of theoretical ideas with the possibilities offered by technology can make the decisions in organisations more rational and, at the same time, more human.

For many small businesses, organisations, clubs, artists, faith groups, voluntary organisations/charities and sole traders, applying the General Data Protection Regulation (GDPR) has been like playing a game of "Snakes and Ladders". As soon as you move along the board and climb a ladder, a snake appears, which takes you right back to where you started. Conflicting advice abounds and there is nowhere for these individuals to go for simple answers all in one place. With the threat of fines seeming around every corner, now more than ever is the time for smaller organisations to get to grips with GDPR so that they can demonstrate their compliance. GDPR: A Game of Snakes and Ladders is an easy to read reference tool, which uses simple language in bite size easily signposted chapters. Adopting a no-nonsense approach, the Regulation is explained so that organisations can comply with the minimum of fuss and deliver this compliance in the shortest timeframe without the need to resort to expensive consultants or additional staff. The book is supported by a variety of easy to follow case studies, example documents and fact sheets. The author signposts warnings and important requirements (snakes) and hints and suggestions (ladders) and also provides a section on staff training and a Game of Snakes and Ladders training slide pack. Additional resources are available on the companion website. This user-friendly book, written by a Data Protection Officer and business management specialist will help you understand the Regulation, where it applies in your organisation and how to achieve compliance (and win at the compliance game).

This textbook is about computer science. It is also about Python. However, there is much more. The study of algorithms and data structures is central to understanding what computer science is all about. Learning computer science is not unlike learning any other type of difficult subject matter. The only way to be successful is through deliberate and incremental exposure to the fundamental ideas. A beginning computer scientist needs practice so that there is a thorough understanding before continuing on to the more complex parts of the curriculum. In addition, a beginner needs to be given the opportunity to be successful and gain confidence. This textbook is designed to serve as a text for a first course on data structures and algorithms, typically taught as the second course in the computer science curriculum. Even though the second course is considered more advanced than the first course, this book assumes you are beginners at this level. You may still be struggling with some of the basic ideas and skills from a first computer science course and yet be ready to further explore the discipline and continue to practice problem solving. The authors cover abstract data types and data structures, writing algorithms, and solving problems. We look at a number of data structures and solve classic problems that arise. The tools and techniques that you learn here will be applied over and over as you continue your study of computer science. This textbook has three key features: - A strong focus on problem solving introduces students to the fundamental data structures and algorithms by providing a very readable text without introducing an overwhelming amount of new language syntax. - Algorithm analysis in terms of Big-O running time is introduced early and applied throughout. - Python is used to facilitate the success of beginning students in using and mastering data structures and algorithms.

Artificial Intelligence in Information and Communication Technologies, Healthcare and Education: A Roadmap Ahead is designed as a reference text and discusses inter-dependability, communication and effective control for the betterment of services through artificial intelligence (AI), as well as the challenges and path ahead for AI in computing and control across different domains of business and human life. The book accommodates technologies and application domains including backbone hardware, systems and methods for deployment, which help incorporating intelligence through different supervised and probabilistic learning approaches. Features The book attempts to establish a connection between hardware, software technologies and algorithmic intelligence for data analysis and decision support in domains such as healthcare, education and other aspects of business and mobility. It presents various recent applications of artificial intelligence in information and communication technologies such as search and optimization methods, machine learning, data representation and ontologies, and multi-agent systems. The book provides a collection of different case studies with experimentation results than mere theoretical and generalized approaches. Covers most of the applications using the trending technologies like machine learning (ML), data science (DS), Internet of Things (IoT), and underlying information and communication technologies. The book is aimed primarily at advanced undergraduates and postgraduate students studying computer science, computer applications, and information technology. Researchers and professionals will also find this book useful.

The Turing/von Neumann model of computing is dominant today but is by no means the only one. This textbook explores an important subset of alternatives, including those such as quantum and neuromorphic, which receive daily news attention. The models are organized into distinct groups. After a review of the Turing/von Neumann model to set the stage, the author discusses those that have their roots in the Turing/von Neumann model but perform potentially large numbers of computations in parallel; models that do away with the preplanned nature of the classical model and compute from just a statement of the problem; others that are simply mathematically different, such as probabilistic and reversible computation; models based on physical phenomena such as neurons; and finally those that leverage unique physical phenomena directly, such as quantum, optical, and DNA-based computing. Suggested readings provide a jumping-off point for deeper learning. A supplemental website contains chapters that did not make it into the book, as well as exercises, projects, and additional resources that will be useful for more in-depth investigations. The Zen of Exotic Computing is intended for computer science students interested in understanding alternative models of computing. It will also be of interest to researchers and practitioners interested in emerging technology such as quantum computing, machine learning, and AI.

A comprehensive reference book for detailed explanations for every algorithm and techniques related to the transformers. 60+ transformer architectures covered in a comprehensive manner. A book for understanding how to apply the transformer techniques in speech, text, time series, and computer vision. Practical tips and tricks for each architecture and how to use it in the real world. Hands-on case studies and code snippets for theory and practical real-world analysis using the tools and libraries, all ready to run in Google Colab.

Focuses on the definition, engineering, and delivery of AI solutions as opposed to AI itself Reader will still gain a strong understanding of AI, but through the perspective of delivering real solutions Explores the core AI issues that impact the success of an overall solution including i. realities of dealing with data, ii. impact of AI accuracy on the ability of the solution to meet business objectives, iii. challenges in managing the quality of machine learning models Includes real world examples of enterprise scale solutions Provides a series of (optional) technical deep dives and thought experiments.

Includes PDE Modeler interface including example solutions of the two- and three dimensional PDEs * Presents methodology for all the types of Partial Differential Equations, representative of any engineering problem * Describes the ODE solver for the IVP and BVP problems by the practical examples from mechanics and thermodynamic properties of materials * Covers the basics of MATLAB (R) to solve both ordinary and partial differential equations * Reviews spatially one dimensional PDE solver with actual engineering examples

This book proposes a new critical relationship between computation and architecture, developing a history and theory of representation in architecture to understand and unleash potential means to open up creativity in the field. Historically, architecture has led spatial representation. Today, computation has established new representational paradigms that can be compared to spatial representations, such as the revolution of perspective in the Renaissance. Architects now use software, robotics, and fabrication tools with very little understanding and participation in how these tools influence, revolutionize, and determine both architecture and its construction today. Why does the discipline of architecture not have a higher degree of authorship in the conception and development of computational technologies that define spatial representation? This book critically explores the relationship between history, theory and cultural criticism. Lorenzo-Eiroa positions new understandings through parallel historical sections and theories of many revolutionary representational architecture canons displaced by conventional spatial projection. He identifies the architects, artists, mathematicians, and philosophers that were able to revolutionise their disciplines through the development of new technologies, new systems of representation, and new lenses to understand reality. This book frames the discussion by addressing new means to understand and expand architecture authorship in relation to survey, information, representation, higher dimensional space, Big Data, and Artificial Intelligence - in the pursuit of activating an architecture of information. This will be important reading for upper-level students and researchers of architecture and architectural theory, especially those with a keen interest in computational design and robotic fabrication.

Describes the contribution of soft computing techniques towards a new paradigm shift Explores Soft Computing techniques in a systematic manner starting from their initial stage to recent developments in this area Presents a systematic application of fuzzy logic in mathematical sciences and decision-making. Examines the application of soft computing in health sciences and in the modeling of epidemics including the effects of vaccination Discusses the application of soft computing techniques in the modeling of infectious diseases

Focuses on the definition, engineering, and delivery of AI solutions as opposed to AI itself Reader will still gain a strong understanding of AI, but through the perspective of delivering real solutions Explores the core AI issues that impact the success of an overall solution including i. realities of dealing with data, ii. impact of AI accuracy on the ability of the solution to meet business objectives, iii. challenges in managing the quality of machine learning models Includes real world examples of enterprise scale solutions Provides a series of (optional) technical deep dives and thought experiments.

Get ahead of the curve--learn about big data on the blockchain Blockchain came to prominence as the disruptive technology that made cryptocurrencies work. Now, data pros are using blockchain technology for faster real-time analysis, better data security, and more accurate predictions. Blockchain Data Analytics For Dummies is your quick-start guide to harnessing the potential of blockchain. Inside this book, technologists, executives, and data managers will find information and inspiration to adopt blockchain as a big data tool. Blockchain expert Michael G. Solomon shares his insight on what the blockchain is and how this new tech is poised to disrupt data. Set your organization on the cutting edge of analytics, before your competitors get there! Learn how blockchain technologies work and how they can integrate with big data Discover the power and potential of blockchain analytics Establish data models and quickly mine for insights and results Create data visualizations from blockchain analysis Discover how blockchains are disrupting the data world with this exciting title in the trusted For Dummies line!

ITIL is the leading best-practice framework for ITSM (IT service management) and is globally adopted in both the public and private sectors. The latest evolution of the framework - ITIL 4 - has been significantly updated and addresses new ITSM challenges, includes new technologies and incorporates new ways of working. ITIL 4 has evolved to a value system-focused approach that can be integrated with other management practices and ways of working, such as Agile and DevOps. Its end-to-end digital operation model has been designed to help IT teams create, deliver and operate technical products and services that fit their organisation's wider business strategy. ITIL(R) 4 Essentials contains everything you need to know to pass the ITIL 4 Foundation Certificate, plus more. It covers practices and concepts that are not addressed as part of the Foundation syllabus, making it ideal for newly qualified practitioners. The book offers practical tips - based on the author's extensive experience - for applying service management in the real world, with symbols used throughout to highlight which content is related to the ITIL 4 Foundation syllabus and which is not. Ideal for self-study candidates and training participants, ITIL 4 Essentials will prove a helpful companion to their studies and a practical aid for their professional development. Project managers, contractors or consultants with limited study time will also find it essential to their part-time education. This second edition has been updated to align with amendments to the ITIL(R) 4 Foundation syllabus, including: Replacing 'change control' with 'change enablement' throughout; The removal of 'IT' from the definition of a change; and Updating definitions for customer, sponsor and user. A perfect companion before, during and after your ITIL exam - buy your copy today. ITIL(R) is a registered trademark of AXELOS Limited. All rights reserved. This book is an official AXELOS licensed product.