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See below for a selection of the latest books from Computer science category. Presented with a red border are the Computer science books that have been lovingly read and reviewed by the experts at Lovereading. With expert reading recommendations made by people with a passion for books and some unique features Lovereading will help you find great Computer science books and those from many more genres to read that will keep you inspired and entertained. And it's all free!
Harness the power of Apple iOS machine learning (ML) capabilities and learn the concepts and techniques necessary to be a successful Apple iOS machine learning practitioner! Machine earning (ML) is the science of getting computers to act without being explicitly programmed. A branch of Artificial Intelligence (AI), machine learning techniques offer ways to identify trends, forecast behavior, and make recommendations. The Apple iOS Software Development Kit (SDK) allows developers to integrate ML services, such as speech recognition and language translation, into mobile devices, most of which can be used in multi-cloud settings. Focusing on Apple's ML services, Machine Learning for iOS Developers is an up-to-date introduction to the field, instructing readers to implement machine learning in iOS applications. Assuming no prior experience with machine learning, this reader-friendly guide offers expert instruction and practical examples of ML integration in iOS. Organized into two sections, the book's clearly-written chapters first cover fundamental ML concepts, the different types of ML systems, their practical uses, and the potential challenges of ML solutions. The second section teaches readers to use models--both pre-trained and user-built--with Apple's CoreML framework. Source code examples are provided for readers to download and use in their own projects. This book helps readers: Understand the theoretical concepts and practical applications of machine learning used in predictive data analytics Build, deploy, and maintain ML systems for tasks such as model validation, optimization, scalability, and real-time streaming Develop skills in data acquisition and modeling, classification, and regression. Compare traditional vs. ML approaches, and machine learning on handsets vs. machine learning as a service (MLaaS) Implement decision tree based models, an instance-based machine learning system, and integrate Scikit-learn & Keras models with CoreML Machine Learning for iOS Developers is a must-have resource software engineers and mobile solutions architects wishing to learn ML concepts and implement machine learning on iOS Apps.
If there is no debate on how huge is the impact of digital technologies on human activities, few reflect on the underlying patterns on which digital innovation relies. The field of sociotechnology (see Wiebe E. Bijker and Jhon Law) and sociology of innovation (see Michel Callon and Bruno Latour) offers a coherent framework to think about the relationship between technology and society. Indeed, producing new devices or applications transforms practices and potentialities, and consequently, the ground of reality from which organization and people interact. The aim of this book is to propose a state of the art on the effects of current and prototypal digital technologies on human activities on the one hand, and to report two concrete case studies regarding ICT for higher education and the Internet of Things. How digital data and media reconfigure perceptions, actions and collective thinking? How the Internet of Things could revolutionize management? How dematerialized and automated communications transcend physical borders? Discussing both the engineering and the practical aspects of these questions, the author defines key indicators related to four majors properties of digital frontiers: the capta dimension (collecting information), the data dimension (treating information), the media dimension (representing information) and the acta dimension (using information). The author also proposes prospective results of the e-transformation of modern societies.
This series is for the Cambridge International AS & A Level Computer Science syllabus (9618) for examination from 2021. Developed by an experienced author and examiner team, this revision guide accompanies the coursebook and is written for the Cambridge International AS & A Level Computer Science syllabus (9618). It encourages students to practise their skills to help prepare them for the examination. The guide provides all the explanations to concepts that students have learnt throughout the course with a wealth of extra practice opportunities. Answers to questions are at the back of the book, so students are free to study in their own time.
We are working with Cambridge Assessment International Education to gain endorsement for this forthcoming title. Reinforce learning and deepen understanding of the key concepts covered in the Cambridge International AS & A Level Computer Science syllabus (9618); an ideal course companion or homework book for use throughout the course. - Build confidence with a variety of problems with increasing complexity and depth to be solved using formal methods that include structured English, pseudocode, flowcharts and writing programs. - Keep track of students' work with ready-to-go write-in exercises. - Save time with all answers available in the Online Teacher's Guide. Also available in the series Student Book ISBN: 9781510457591 Student eTextbook ISBN: 9781510457614 Whiteboard eTextbook ISBN: 9781510457621 Online Teacher's guide ISBN: 9781510457652
With respect to the ever-increasing developments in artificial intelligence and artificial neural network applications in different scopes such as medicine, biology, history, military industries, recognition science, space, machine learning and etc., Neural Networks: History and Applications first presents a comprehensive investigation of artificial neural networks. Next, the authors focus on studies carried out with the artificial neural network approach on the emotion recognition from 2D facial expressions between 2009 and 2019. The major objective of this study is to review, identify, evaluate and analyze the performance of artificial neural network models in emotion recognition applications. This compilation also proposes a simple nonlinear approach for dipole mode index prediction where past values of dipole mode index were used as inputs, and future values were predicted by artificial neural networks. The study was also conducted for seasonal dipole mode index prediction because the dipole mode index is more prominent in the Sep-Oct-Nov season. A subsequent study focuses on how mammography has a high false negative and false positive rate. As such, computer-aided diagnosis systems have been commercialized to help in micro-calcification detection and malignancy differentiation. Yet, little has been explored in differentiating breast cancers with artificial neural networks, one example of computer-aided diagnosis systems. The authors aim to bridge this gap in research. The penultimate chapter reviews the general conditions under which synaptic plasticity most effectively takes place to support the supervised learning of a precise temporal code. Then, the accuracy of each plasticity rule with respect to its temporal encoding precision is examined, and the maximum number of input patterns it can memorize using the precise timings of individual spikes as an indicator of storage capacity in different control and recognition tasks is explored. In closing, a case study is presented centered on an intelligent decision support system that is built on a neural network model based on the Encog machine learning framework to predict cryptocurrency close prices.
Unexpected and extreme natural hazards resulting from the Earth's natural processes can be harmful to humans. As a result, powerful approaches have been developed to apply advanced machine learning and big data methods for extracting relevant patterns, high performance computing, and data visualization to the field of natural hazards. Machine Learning for Natural Hazards shares recent advances in the field, with emphasis on issues addressed by advanced machine learning and big data analytic techniques. This book aims to provide practitioners with efficient and effective tools to deal with natural hazard related data. Relevant, illustrative, study cases are also presented and discussed.
An accessible guide to the ideas and technologies underlying such applications as GPS, Google Maps, Pokemon Go, ride-sharing, driverless cars, and drone surveillance. Billions of people around the globe use various applications of spatial computing daily-by using a ride-sharing app, GPS, the e911 system, social media check-ins, even Pokemon Go. Scientists and researchers use spatial computing to track diseases, map the bottom of the oceans, chart the behavior of endangered species, and create election maps in real time. Drones and driverless cars use a variety of spatial computing technologies. Spatial computing works by understanding the physical world, knowing and communicating our relation to places in that world, and navigating through those places. It has changed our lives and infrastructures profoundly, marking a significant shift in how we make our way in the world. This volume in the MIT Essential Knowledge series explains the technologies and ideas behind spatial computing. The book offers accessible descriptions of GPS and location-based services, including the use of Wi-Fi, Bluetooth, and RFID for position determination out of satellite range; remote sensing, which uses satellite and aerial platforms to monitor such varied phenomena as global food production, the effects of climate change, and subsurface natural resources on other planets; geographic information systems (GIS), which store, analyze, and visualize spatial data; spatial databases, which store multiple forms of spatial data; and spatial statistics and spatial data science, used to analyze location-related data.
Provides comprehensive coverage of the current state of IoT, focusing on data processing infrastructure and techniques Written by experts in the field, this book addresses the IoT technology stack, from connectivity through data platforms to end-user case studies, and considers the tradeoffs between business needs and data security and privacy throughout. There is a particular emphasis on data processing technologies that enable the extraction of actionable insights from data to inform improved decision making. These include artificial intelligence techniques such as stream processing, deep learning and knowledge graphs, as well as data interoperability and the key aspects of privacy, security and trust. Additional aspects covered include: creating and supporting IoT ecosystems; edge computing; data mining of sensor datasets; and crowd-sourcing, amongst others. The book also presents several sections featuring use cases across a range of application areas such as smart energy, transportation, smart factories, and more. The book concludes with a chapter on key considerations when deploying IoT technologies in the enterprise, followed by a brief review of future research directions and challenges. The Internet of Things: From Data to Insight Provides a comprehensive overview of the Internet of Things technology stack with focus on data driven aspects from data modelling and processing to presentation for decision making Explains how IoT technology is applied in practice and the benefits being delivered. Acquaints readers that are new to the area with concepts, components, technologies, and verticals related to and enabled by IoT Gives IoT specialists a deeper insight into data and decision-making aspects as well as novel technologies and application areas Analyzes and presents important emerging technologies for the IoT arena Shows how different objects and devices can be connected to decision making processes at various levels of abstraction The Internet of Things: From Data to Insight will appeal to a wide audience, including IT and network specialists seeking a broad and complete understanding of IoT, CIOs and CIO teams, researchers in IoT and related fields, final year undergraduates, graduate students, post-graduates, and IT and science media professionals.
Artificial Intelligence is all around us - in the news, in our homes, in our phones, in our cars - everywhere. While AI is becoming more ubiquitous in our daily lives, many people don't have a fair understanding of what AI is and how it works. This book aims to address this gap in knowledge by giving readers a pocket guide to the world of AI. Features: * Provides an accessible and easy-to-understand guide to AI for non-technical readers * Covers basic concepts in AI, their history, and the inspirations that helped them to materialize * Describes what AI is, where to find it, how scientists try to evaluate it, and the main limitations for AI * Explores the most popular AI techniques in a very readable and comprehensible way, using anecdotes and simple examples This book is accessible for all. It will be valuable to teachers who wish to enrich their classes with some interesting and popular topics; sales managers and business analysts who wish to better understand the IT world; and finally, politicians and journalists who take part in debates on latest technologies. Jedrzej Osinski earned a PhD in Artificial Intelligence and has published 14 scientific papers to date as well as co-authoring two books. He has over ten years of experience working in IT companies of different sizes, domains (web, telecom, banking, e-learning), organisation structure and locations (Poland, Ireland, UK).
Information Engineering for Port and Marine Environments provides the technology of tidal level prediction, the technology of oil spill early-warning, and the research for the theory of storm sedimentation, the construction for monitor ability, the early-warning service for numerical simulation and operational, which involves many aspects such as theoretical research, system establishment, and application of information technology, et al. Because of the certain prospective and advancement of multiple work, it will play a positive role in promoting the related technology of the field. There are several of important offshore ports in China, such as Tianjin port, Yangshan Port, Ningbo-Zhoushan port, Huanghua port et al., most of them are located in the coast of muddy and muddy silty, and the depth of water is shallow, the sediment deposition is serious, the large ship is operated by tide. In order to sufficiently keep the rapid and stable economic growth in bay, estuary and delta, guarantee the security of port, channel, maritime, oceanic engineering and resource development of oil and gas, and better escort for the social economy activities, it is essential to provide the information service of sediment and ocean hydrometeorology with width coverage, and forecasting and warning information. It is all the latest research results in the book, which involves many fields such as physical oceanography, meteorology, biology, chemistry, geology, environment, transportation and law and so on. The development of information assurance and prediction system for port shipping and ocean environment is a huge and arduous project. It is too hasty to finish the book, due to the limited knowledge of the author, the careless is unavoidable, cordially invites the readers to point out. Features: An entire system to forecast the port shipping and ocean environment information is proposed, including what is the port shipping and ocean environment information. The concept of port shipping and ocean environment data integration is presented, and the essential modules are built for the ocean dynamics model. The high performance port shipping and ocean environment data processing system is constructed, and the model dataset and geographic information is obtained to build the basic database. The application of information assurance technology for port shipping and ocean environment is conducted at Tianjin port and Yangshan Port. This book is meant for senior undergraduates and postgraduate students in the fields of geoinformatics, Port engineering and Marine engineering. Engineers and technicians in the related fields can also use it for reference.
Artificial Intelligence is all around us - in the news, in our homes, in our phones, in our cars - everywhere. While AI is becoming more ubiquitous in our daily lives, many people don't have a fair understanding of what AI is and how it works. This book aims to address this gap in knowledge by giving readers a pocket guide to the world of AI. Features * Provides an accessible and easy to understand guide to AI for non-technical readers * Covers basic concepts in AI, their history, and the inspirations that helped them to materialize * Describes what AI is, where to find it, how scientists try to evaluate it, and the main limitations for AI * Explores the most popular AI techniques in a very readable and easy to understand way, using anecdotes and simple examples This book is accessible for all. The book would be valuable to teachers who wish to enrich their classes with some interesting and popular topics, sales managers and business analysts who wish to understand better the IT world, and finally politicians and journalists who take part in debates on latest technologies. Jedrzej Osinski has a Ph.D. in Artificial Intelligence and has published 14 scientific papers to date as well being the co-author of two books. He has over ten years of experience working in IT companies of different sizes, domains (web, telecom, banking, e-learning), organisation structure and locations (Poland, Ireland, UK).
Cloud computing enables on-demand access to shared computing resources providing services more quickly and at a lower cost than having agencies maintain these resources themselves. Chapter 1 discusses selected agencies' progress in implementing cloud services, the extent to which those agencies increased cloud service spending and achieved savings or cost avoidances, and examples of agency-reported cloud investments with notable benefits. The Office of Management and Budget (OMB) has developed a new strategy to accelerate agency adoption of cloud-based solutions: Cloud Smart. Chapter 2 reports on the strategy of successful cloud adoption: security, procurement, and workforce. The Department of Defense (DoD) has entered the modern age of warfighting where the battlefield exists as much in the digital world as it does in the physical. Cloud is a fundamental component of the global infrastructure that will empower the warfighter with data and is critical to maintaining our military's technological advantage as reported in chapter 3. Chapter 4 discusses accelerated adoption of the Joint Enterprise Defense Infrastructure (JEDI) Cloud program. In the Clarifying Lawful Overseas Use of Data (CLOUD) Act, Congress enacted one of the first major changes in years to U.S. law governing cross-border access to electronic communications held by private companies. Chapter 5 reports on the major components of the CLOUD Act. Chapter 6 discusses United States v. Microsoft Corp as it pertains to the CLOUD Act.