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Summary: "Learn about the everyday uses and benefits of artificial intelligence, as well as the risks and dangers that come with it"-- Provided by publisher.

Summary: Artificial Intelligence (AI) gets your system to think smart and learn intelligently. This book is packed with some of the smartest trending examples with which you will learn the fundamentals of AI. By the end, you will have acquired the basics of AI by practically applying the examples in this book.

Summary: Artificial intelligence (AI) has landed on Earth like an alien spacecraft from a science fiction novel. We now have self-driving cars; computers that can diagnose illnesses, recommend treatments, and predict and solve crimes; smart phones that can route us from point A to point B; gadgets that can understand and respond to spoken commands; and much more. All of this is made possible by machine learning (ML). Although AI and ML can be used to help us answer questions and solve problems, for many of us they create more questions than answers, questions such as “What is intelligence?” “How do machines learn?” “What is a machine learning algorithm, and how does it work?” “Will machines take my job?” “Will they take over the world?” and, for those in business, “What do I need to know about AI and ML to harness its power?” This book tackles those questions and more as it brings you up to speed on the basics of AI, ML, and artificial neural networks. You begin by reading the story of AI that traces its evolution from the early 1950s to the present, revealing many of the core ideas that continue to drive its development. You explore recent technological innovations that have reinvigorated the field by providing the “big data” that makes machine learning so powerful — innovations such as GPS, social media and electronic transactions. And you discover how machines learn through the use of powerful processing combined with machine learning algorithms and artificial neural networks that mimic the function of the human brain. All of these ideas are discussed against a backdrop of potential new business opportunities and technologies, so you can begin to harness the power of AI to achieve and maintain competitive advantage.

Summary: Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare covers exciting developments at the intersection of computer science and statistics. While much of machine-learning is statistics-based, achievements in deep learning for image and language processing rely on computer sciences use of big data. Aimed at those with a statistical background who want to use their strengths in pursuing AI research, the book: Covers broad AI topics in drug development, precision medicine, and healthcare. Elaborates on supervised, unsupervised, reinforcement, and evolutionary learning methods. Introduces the similarity principle and related AI methods for both big and small data problems. Offers a balance of statistical and algorithm-based approaches to AI. Provides examples and real-world applications with hands-on R code. Suggests the path forward for AI in medicine and artificial general intelligence. As well as covering the history of AI and the innovative ideas, methodologies and software implementation of the field, the book offers a comprehensive review of AI applications in medical sciences. In addition, readers will benefit from hands on exercises, with included R code.

Abstract: Artificial Intelligence (AI) for security management explores terminologies of security and how AI can be applied to automate security processes. Additionally, the text provides detailed explanations and recommendations for how implement procedures. Practical examples and real-time use cases are evaluated and suggest appropriate algorithms based on the author's experiences. Threat and associated securities from the data, process, people, things (e.g., Internet of things), systems, and actions were used to develop security knowledge base, which will help readers to build their own knowledge base. This book will help the readers to start their AI journey on security and how data can be applied to drive business actions to build secure environment.

Summary: Artificial Intelligence in Cancer: Diagnostic to Tailored Treatment provides theoretical concepts and practical techniques of AI and its applications in cancer management, building a roadmap on how to use AI in cancer at different stages of healthcare.

Summary: Many industries have been revolutionized by the widespread adoption of AI and machine learning. The programmatic availability of historical and real-time financial data in combination with techniques from AI and machine learning will also change the financial industry in a fundamental way. This practical book explains 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 how machine and deep learning algorithms can be applied to finance.

Summary: "Targeting Chronic Inflammatory Lung Diseases Using Advanced Drug Delivery Systems explores the development of novel therapeutics and diagnostics to improve pulmonary disease management, looking down to the nanoscale level for an efficient system of targeting and managing respiratory disease. The book examines numerous nanoparticle-based drug systems such as nanocrystals, dendrimers, polymeric micelles, protein-based, carbon nanotube, and liposomes that can offer advantages over traditional drug delivery systems. Starting with a brief introduction on different types of nanoparticles in respiratory disease conditions, the book then focuses on current trends in disease pathology that use different in vitro and in vivo models. The comprehensive resource is designed for those new to the field and to specialized scientists and researchers involved in pulmonary research and drug development"-- Provided by publisher.

Summary: The book discusses topics such as cognitive computing and emotional intelligence, big data analysis, clinical decision support systems, deep learning, personal omics, digital health, predictive models, prediction of epidemics, drug discovery, precision nutrition and fitness. Additionally, there is a section dedicated to discuss and analyze AI products related to precision healthcare already available"--Publisher's description.

Summary: "To understand the dynamic patterns of behaviours and interactions between athletes that characterise successful performance in different sports is an important challenge for all sport practitioners. This book guides the reader in understanding how an ecological dynamics framework for use of artificial intelligence (AI) can be implemented to interpret sport performance and the design of practice contexts. By examining how AI methodologies are utilised in team games, such as football, as well as individual sports, such as golf and climbing, this book provides a better understanding of the kinematic and physiological indicators that might better capture athletic performance by looking at the current state-of-the-art AI approaches. Artificial Intelligence in Sport Performance Analysis provides an all-encompassing perspective in an innovative approach that signals practical applications for both academics and practitioners in the fields of coaching, sports analysis, sport science as well as related subjects such as engineering, computer and data science, and statistics"-- Provided by publisher.

Summary: The main objective of this book is to provide a common platform for diverse concepts in satellite image processing. In particular it presents the state-of-the-art in Artificial Intelligence (AI) methodologies and shares findings that can be translated into real-time applications to benefit humankind. Interdisciplinary in its scope, the book will be of interest to both newcomers and experienced scientists working in the fields of satellite image processing, geo-engineering, remote sensing and Artificial Intelligence. It can be also used as a supplementary textbook for graduate students in various engineering branches related to image processing. .

Summary: This book includes research articles and expository papers on the applications of artificial intelligence and big data analytics to battle the pandemic. In the context of COVID-19, this book focuses on how big data analytic and artificial intelligence help fight COVID-19. The book is divided into four parts. The first part discusses the forecasting and visualization of the COVID-19 data. The second part describes applications of artificial intelligence in the COVID-19 diagnosis of chest X-Ray imaging. The third part discusses the insights of artificial intelligence to stop spread of COVID-19, while the last part presents deep learning and big data analytics which help fight the COVID-19. .

Summary: This book discusses how Big Data could be implemented in educational settings and research, using empirical data and suggesting both best practices and areas in which to invest future research and development. It also explores: 1) the use of learning analytics to improve learning and teaching; 2) the opportunities and challenges of learning analytics in education. As Big Data becomes a common part of the fabric of our world, education and research are challenged to use this data to improve educational and research systems, and also are tasked with teaching coming generations to deal with Big Data both effectively and ethically. The Big Data era is changing the data landscape for statistical analysis, the ways in which data is captured and presented, and the necessary level of statistical literacy to analyse and interpret data for future decision making. The advent of Big Data accentuates the need to enable citizens to develop statistical skills, thinking and reasoning needed for representing, integrating and exploring complex information. This book offers guidance to researchers who are seeking suitable topics to explore. It presents research into the skills needed by data practitioners (data analysts, data managers, statisticians, and data consumers, academics), and provides insights into the statistical skills, thinking and reasoning needed by educators and researchers in the future to work with Big Data. This book serves as a concise reference for policymakers, who must make critical decisions regarding funding and applications. .

Summary: A biological neural network passes information between receptors and effectors by using electrical impulses. Neural networks are a collection of neurons that allow the body to process various stimuli and respond to them. Signals passed between neurons are either inhibitory or excitatory, and an action potential is initiated when the excitatory signals reach threshold potential. This book is compiled in such a manner, that it will provide in-depth knowledge about the theory and practice of brain theory and neural networks. With state-of-the-art inputs by acclaimed experts of this field, this book targets students and professionals.

Summary: Evolve your traditional intranet platform into a next-generation digital workspace with this comprehensive book. Through in-depth coverage of strategies, methods, and case studies, you will learn how to design and build an employee experience platform (EXP) for improved employee productivity, engagement, and collaboration. In Build a Next-Generation Digital Workplace, author Dr. Shailesh Kumar Shivakumar takes you through the advantages of EXPs and shows you how to successfully implement one in your organization. This book provides extensive coverage of topics such as EXP design, user experience, content strategy, integration, EXP development, collaboration, and EXP governance. Real-world case studies are also presented to explore practical applications. Employee experience platforms play a vital role in engaging, empowering, and retaining the employees of an organization. Next-generation workplaces demand constant innovation and responsiveness, and this book readies you to fulfill that need with an employee experience platform. You will: Understand key design elements of EXP, including the visual design, EXP strategy, EXP transformation themes, information architecture, and navigation design. Gain insights into end-to-end EXP topics needed to successfully design, implement, and maintain next-generation digital workplace platforms. Study methods used in the EXP lifecycle, such as requirements and design, development, governance, and maintenance Execute the main steps involved in digital transformation of legacy intranet platforms to EXP. Discover emerging trends in digital workplace such as gamification, machine-led operations model and maintenance model, employee-centric design (including persona based design and employee journey mapping), cloud transformation, and design transformation. Comprehend proven methods for legacy Intranet modernization, collaboration, solution validation, migration, and more.

Summary: Learn how to build a design system framed within the context of your specific business needs. This book guides you through the process of defining a design language that can be understood across teams, while also establishing communication strategies for how to sell your system to key stakeholders and other contributors. With a defined set of components and guidelines, designers can focus their efforts on solving user needs rather than recreating elements and reinventing solutions. You'll learn how to use an interface inventory to surface inconsistencies and inefficient solutions, as well as how to establish a component library by documenting existing patterns and creating new ones. You'll also see how the creation of self-documenting styles and components will streamline your UX process. Building Design Systems provides critical insights into how to set up a design system within your organization, measure the effectiveness of that system, and maintain it over time. You will develop the skills needed to approach your design process systematically, ensuring that your design system achieves the purpose of your organization, your product, and your team. What You'll Learn Develop communication strategies necessary to gain buy-in from key stakeholders and other teams Establish principles based on your specific needs Design, build, implement, and maintain a design system from the ground up Measure the effectiveness of your system over time Who This Book Is For All teams, large and small, seeking to unify their design language through a cohesive design system and create buy-in for design thinking within their organization; UX, visual, and interaction designers, as well as product managers and front-end developers will benefit from a systematic approach to design.

Summary: "This book examines the latest advances and trends in computer vision and machine learning algorithms for various applications"-- Provided by publisher.

Summary: "This groundbreaking collection advances understanding of the concept of media practices by critically interrogating its relevance for the study of citizen and activist media. Media as practice has emerged as a powerful approach to understanding the media's significance in contemporary society. Bringing together contributions from leading scholars in sociology, media and communication, social movement and critical data studies, this book stimulates dialogue across previously separate traditions of research on citizen and activist media practices and stakes out future directions for research in this burgeoning interdisciplinary field. Framed by a foreword by Nick Couldry and a substantial introductory chapter by the editors, contributions to the volume trace the roots and appropriations of the concept of media practice in Latin American communication theory; reflect on the relationship between activist agency and technological affordances; explore the relevance of the media practice approach for the study of media activism, including activism that takes media as its central object of struggle; and demonstrate the significance of the media practice approach for understanding processes of mediatization and datafication. Offering both a comprehensive introduction to scholarship on citizen media and practice and a cutting-edge exploration of a novel theoretical framework, the book is ideal for students and experienced scholars alike"-- Provided by publisher.

Summary: "CITIZENS OF SCANDAL traces the shifting relationship between civil society, national print media, and public officials in late twentieth-century Mexico. As Vanessa Freije shows, from the 1960s through the 1980s, an increasing number of reporters in Mexico denounced corruption. Freije argues that the circulation of investigative reporting had transformative effects on Mexican political culture and urban citizenship. For one thing, the publicity of wrongdoing altered political practice by undermining state attempts to manage public discourse. Additionally, publicizing official wrongdoing centered collective attention and forged new political subjectivities. Freije thus exposes how publicity became an important, though unpredictable and inequitable, tool of Mexican political citizenship. Despite the increased transparency of information, reporters often withheld many secrets from public discussion, sometimes out of concern for their safety. These tensions-between transparency and secrecy, representation and exclusion, and free speech and censorship-defined the Mexican public sphere in the late-twentieth century as presented in the book. The chapters take on a variety of temporal and geographical scales to examine widely-circulated stories in the Mexican national public. Chapter 1 examines how Mexico City journalists and the broader public reckoned with the limits of state-led development, and, by extension, the Mexican Revolution. Chapter 4 takes up the iconic scandal of Arturo "el Negro" Durazo, Mexico City's chief of police (1976-1982) who was embroiled in drug trafficking, embezzlement, and most dramatically, murder. These popular media often gave racialized and gendered explanations of corruption, which influenced the broader Mexican imaginary. Chapter 6 analyzes local, national, and international coverage of the 1986 gubernatorial elections in the northern state of Chihuahua. These and the other news stories explored in the book raise thorny questions about the politics of scandal, revealing that many readers and reporters understood the press as an advocate that could not (and should not) be objective"-- Provided by publisher.

Summary: Learn how to make better decisions and write cleaner Ruby code. This book shows you how to avoid messy code that is hard to test and which cripples productivity. Author Carleton DiLeo shares hard-learned lessons gained from years of experience across numerous codebases both large and small. Each chapter covers the topics you need to know to make better decisions and optimize your productivity. Many books will tell you how to do something; this book will tell you why you should do it. Start writing code you love. What You Will Learn Build better classes to help promote code reuse Improve your decision making and make better, smarter choices Identify bad code and fixed it Create quality names for all of your variables, classes, and modules Write better, concise classes Improve the quality of your methods Properly use modules Clarify your Boolean logic See when and how you refactor Improve your understanding of TDD and write better tests Who This Book Is For This book is written for Ruby developers. There is no need to learn a new language or translate concepts to Ruby.

Summary: In the era of self-taught developers and programmers, essential topics in the industry are frequently learned without a formal academic foundation. A solid grasp of data structures and algorithms (DSA) is imperative for anyone looking to do professional software development and engineering, but classes in the subject can be dry or spend too much time on theory and unnecessary readings. Regardless of your programming language background, Codeless Data Structures and Algorithms has you covered. In this book, author Armstrong Subero will help you learn DSAs without writing a single line of code. Straightforward explanations and diagrams give you a confident handle on the topic while ensuring you never have to open your code editor, use a compiler, or look at an integrated development environment. Subero introduces you to linear, tree, and hash data structures and gives you important insights behind the most common algorithms that you can directly apply to your own programs. Codeless Data Structures and Algorithms provides you with the knowledge about DSAs that you will need in the professional programming world, without using any complex mathematics or irrelevant information. Whether you are a new developer seeking a basic understanding of the subject or a decision-maker wanting a grasp of algorithms to apply to your projects, this book belongs on your shelf. Quite often, a new, refreshing, and unpretentious approach to a topic is all you need to get inspired.

Summary: Coefficient of Variation (CV) is a unit free index indicating the consistency of the data associated with a real-world process and is simple to mold into computational paradigms. This book provides necessary exposure of computational strategies, properties of CV and extracting the metadata leading to efficient knowledge representation. It also compiles representational and classification strategies based on the CV through illustrative explanations. The potential nature of CV in the context of contemporary Machine Learning strategies and the Big Data paradigms is demonstrated through selected applications. Overall, this book explains statistical parameters and knowledge representation models.

Summary: Colaba, the southernmost tip of Mumbai—a bustling locality with the Gateway of India, the famous Taj Mahal Hotel, and Colaba Causeway, a shopper’s paradise—is the city’s most iconic neighbourhood. But barely 200 years ago, it was a rocky, jackal-infested island, separated from the rest of the great metropolis by a temperamental creek. In this compelling biography, Shabnam Minwalla, journalist, author and long-time resident of the area, tells the tale of the unexpected forces that reshaped land and sea; and allowed this remote corner of Bombay-Mumbai to evolve into one of its liveliest, quirkiest neighbourhoods. Trying to figure out the exact area limits, she unravels accounts of colonial rivalries and dowry negotiations, and of shrewd industrialists who transformed the doomed island into the centre of trade during the cotton boom of the 1860s. She navigates the sometimes charming, sometimes seedy streets to track the area’s evolution from a retreat for British soldiers and sailors to a coveted residential area for the English and Indians alike. She digs into her childhood memories to introduce us to the eccentric Parsis of Cusrow Baug, the warm yet persistent shopkeepers and hawkers of the Causeway, the industrious Sindhis who pioneered co-operative housing societies, the colourful musicians, theatre artists and writers who frequented her corner of Colaba, and the Arabs who come there every year to witness the city’s monsoons. And in a moving section, she records how the neighbourhood rose like a phoenix from the ashes after the 26/11 terrorist attack. Combining a remarkable flair for storytelling with sound journalistic groundwork, and drawing upon three generations of family memory, Shabnam paints an intimate and dynamic portrait of a great and fabled neighbourhood.

Summary: Use the Raspberry Pi and modern computing techniques to build industrial Internet of Things systems. Principles and theoretical aspects of IoT technologies combine with hands-on projects leading to detailed descriptions of several industrial IoT applications. This book presents real-life IoT applications based on the Raspberry Pi, beyond the relatively simplistic demos built for educational purposes or hobbyists. You'll make the transition from tinkering with a couple of sensors and simple devices to building fully developed products for commercial use and industrial systems. You'll also work with sensors and actuators, web technologies used for communications in IoT networks, and the large-scale deployment of IoT software solutions. And see how to design these systems as well as maintain them long term. See the Raspberry Pi in a new light that highlights the true industrial potential of the device. Move beyond connecting an LED to the Raspberry Pi and making it blink to actually managing a network of IoT devices.

Summary: "Contemporary journalism faces a crisis of trust that threatens the institution and may imperil democracy itself. Critics and experts see a renewed commitment to local journalism as one solution. But a lasting restoration of public trust requires a different kind of local journalism than is often imagined, one that engages with and shares power among all sectors of a community. Andrea Wenzel models new practices of community-centered journalism that build trust across boundaries of politics, race, and class, and prioritize solutions while engaging the full range of local stakeholders. Informed by case studies from rural, suburban, and urban settings, Wenzel's blueprint reshapes journalism norms and creates vigorous storytelling networks between all parts of a community. Envisioning a portable, rather than scalable, process, Wenzel proposes a community-centered journalism that, once implemented, will strengthen lines of local communication, reinvigorate civic participation, and forge a trusting partnership between media and the people they cover"-- Provided by publisher.

Summary: "This book is an essential resource exploring the concepts, theories and methods in consumer behaviour specifically applicable to the food and drink sector. Drawing examples from all continents, it provides you with accessible coverage and a truly global perspective of the particular characteristics of this industry"-- Provided by publisher.

Summary: "The early twenty-first century has seen the emergence of a new style of television drama in Britain that adopts the professional practices and production values of high-end American television while remaining emphatically 'British' in content and outlook. This book analyses eight of these dramas - Spooks, Foyle's War, Hustle, Life on Mars, Ashes to Ashes, Downton Abbey, Sherlock and Broadchurch - which have all proved popular with audiences and in their different ways represent the thematic and formal paradigms of post-millennial drama. James Chapman locates new British drama in its institutional and economic contexts, considers their critical and popular reception, and analyses their social politics in relation to their representations of class, gender and nationhood. He demonstrates how contemporary drama has mobilised both new and residual elements in re-configuring genres such as the spy series, cop show and costume drama for the cultural tastes of modern audiences. And it concludes that television drama has played an integral role in both the economic and the cultural export of 'Britishness'"-- Provided by publisher.

Summary: Transform your existing web applications into Google Chrome browser extensions and create brand new extensions that improve your own browsing experience and that of your users. This book shows you how Google Chrome browser extensions are extremely useful tools for enhancing the functionality of the Google Chrome web browser. For example, you can create extensions to summarize the current page you are reading, or to save all of the images in the page you are browsing. They have access to almost all of the features provided by the Google Chrome browser, and they can encapsulate such features in the form of a bundled application providing targeted functionality to users. Extensions also run in a sandboxed environment, making them secure - which is a huge plus in the modern web! The APIs provided by the Chrome Extensions framework help you empower web applications by coupling them with amazing features provided by the Google Chrome web browser, such as bookmarks, history, tabs, actions, storage, notifications, search, and a lot more - facilitating increased productivity on the Google Chrome web browser. You will learn how to: Transform your web application ideas into Google Chrome extensions Choose the recommended components for creating your kind of extension Leverage the power of a Google Chrome browser by making use of the extensions API Showcase your existing web-development skills in a modern way by creating useful extensions.

Summary: This book considers the role journalism education plays in coping with a changing media landscape. It looks at how journalists can empower themselves in an effort to excel in an evolving environment and considers whether it suffices for them to master pre-millennial basic skills or whether brand new competencies need to be incorporated. Few dramatic qualifications are spared when discussing the changes that have shaken the news environment during the noughties. Digitization has both empowered and tried professional journalists through multimedia news production, media convergence and not least a maturing commercial internet. Moreover, digitization has also influenced, and been influenced by, other societal changes such as global financial tensions, evolving multicultural societies, and emerging democracies in search for a suitable journalistic paradigm. Indeed, the rather technological evolutions emphasized time and again, cannot be detached from a cultural setting. This is why an investigation in required competencies benefits from an explicit socio-cultural and cross-continental perspective. As this book tackles a varied set of news ecosystems, it is our hope to offer a nuanced view on what indeed seems to be a global fluidity in journalism practice. Explicit emphasis is put on the role of journalism education as facilitator for, and even innovator in, required journalistic competencies. Time will tell whether or not 'news ecosystems' will again stabilize. This volume makes a number of concrete recommendations towards journalism training and discusses a number of case studies across several continents, illustrating how goals are attuned to a changed news environment. As this book links academic paradigms to concrete journalism practice and education, its reading is recommended both for practitioners and educators.

Summary: "Built using the hands-on and pioneering Missouri Method, this textbook prepares readers to write about and communicate with people of different backgrounds, offering real-world examples of how to practice excellent journalism and strategic communication that takes culture into account. No matter the communication purpose, this book will help readers engage with difference and the concept of fault lines, and to identify and mitigate bias. It provides guidance on communicating the complexity inherent in issues like crime, immigration, and sports, and working with census data to craft stories or strategic campaigns. Above all, the book encourages readers to reconsider assumptions about race, class, gender, identity, sexual orientation, immigration status, religion, disability, and age, and recognize communicators' responsibilities in shaping national discussions. This new edition addresses the ever-changing political and social climate, differentiates excellent journalism from punditry, and shows the business value of understanding diverse perspectives. A fantastic introduction to this complex but important field, this book is perfect for students, teachers, and early career communicators. The combination of a hands-on approach and pull-out boxes with the diverse voices curated by editors María Len-Rios and Earnest Perry make this an ideal text for the classroom and beyond"-- Provided by publisher.

Summary: Find the various relationships among variables that can be present in big data as well as other data sets. This book also covers information entropy, permutation tests, combinatorics, predictor selections, and eigenvalues to give you a well-rounded view of data mining and algorithms in C++. Furthermore, Data Mining Algorithms in C++ includes classic techniques that are widely available in standard statistical packages, such as maximum likelihood factor analysis and varimax rotation. After reading and using this book, you'll come away with many code samples and routines that can be repurposed into your own data mining tools and algorithms toolbox. This will allow you to integrate these techniques in your various data and analysis projects. You will: Discover useful data mining techniques and algorithms using the C++ programming language Carry out permutation tests Work with the various relationships and screening types for these relationships Master predictor selections Use the DATAMINE program.

Summary: Implement real-time data processing applications on the Raspberry Pi. This book uniquely helps you work with data science concepts as part of real-time applications using the Raspberry Pi as a localized cloud. You’ll start with a brief introduction to data science followed by a dedicated look at the fundamental concepts of Python programming. Here you’ll install the software needed for Python programming on the Pi, and then review the various data types and modules available. The next steps are to set up your Pis for gathering real-time data and incorporate the basic operations of data science related to real-time applications. You’ll then combine all these new skills to work with machine learning concepts that will enable your Raspberry Pi to learn from the data it gathers. Case studies round out the book to give you an idea of the range of domains where these concepts can be applied. By the end of Data Science with the Raspberry Pi, you’ll understand that many applications are now dependent upon cloud computing. As Raspberry Pis are cheap, it is easy to use a number of them closer to the sensors gathering the data and restrict the analytics closer to the edge. You’ll find that not only is the Pi an easy entry point to data science, it also provides an elegant solution to cloud computing limitations through localized deployment.

Summary: Business professionals looking to understand the impact, future, and limitations of blockchain need look no further. This revolutionary technology has impacted business and the economy in unprecedented way within the past decade, and it is only continuing to grow. As a leader in your organization, it is vital that you decode blockchain and optimize all the ways in which it can improve your business. Author of Decoding Blockchain for Business, Stijn Van Hijfte, expertly emphasizes the imperative of professionals in any sector of industry to understand the core concepts and implications of blockchain technology. Cryptocurrencies, cryptotrading, and constantly-changing tax structures for financial systems using blockchain technologies are covered in detail. The last effects of blockchain across specific industries such as media, real estate, finance, and regulatory bodies are addressed with an insightful eye from Van Hijfte. If not properly implemented with care and a foundation of knowledge, blockchain brings risks and uncertainties to a company. Know your technology to be ready for the present and the future, and stay ahead of the curve. Blockchain is here to stay, and Decoding Blockchain for Business is your professional roadmap.

Summary: This book presents a wealth of deep-learning algorithms and demonstrates their design process. It also highlights the need for a prudent alignment with the essential characteristics of the nature of learning encountered in the practical problems being tackled. Intended for readers interested in acquiring practical knowledge of analysis, design, and deployment of deep learning solutions to real-world problems, it covers a wide range of the paradigms algorithms and their applications in diverse areas including imaging, seismic tomography, smart grids, surveillance and security, and health care, among others. Featuring systematic and comprehensive discussions on the development processes, their evaluation, and relevance, the book offers insights into fundamental design strategies for algorithms of deep learning.

Summary: Deep learning tools could very well end up with a substantially higher standard of accuracy and reliability in the recognition of physical objects, in some instances more advanced than individual overall human performance. Deep learning is an outlet of understanding, or perhaps studying, that takes advantage of a number of levels of non-linear processor jobs to discover how you can make representations of highly effective daily processes unswervingly from computer data.The first chapter refers to deep learning. Chapter 2 shows that when provided with genomic variance computer data from a variety of people, calculating the chance of complicated populace hereditary designs can often be improbable. Chapter 3 looks at how live-cell imaging provides you with started out a thrilling range into the function cellular heterogeneity performs in vibrant, subsistence devices.Chapter 4 looks at how protein contacts provide you with crucial information and facts for the comprehension of protein frameworks. Chapter 5 suggests a structure for foretelling updates in electronic community end user behavior. Chapter 6 looks at how precise computational recognition of promoters continues to be an issue.Chapter 7 shows that an innovative intrusion detection system ( IDS ) making use of a deep neural network ( DNN ) is offered to improve the safety of in-vehicular system. Chapter 8 looks at how event identification is easily the most basic and also crucial job in event-based all-natural vocabulary processing devices. Chapter 9 looks at getting a grasp on the cell-specific merging designs of transcription factors.Chapter 10 looks at what exactly is the source of our capability to understand orthographic information. Chapter 11 displays comprehending the simplest way to understand blockage at one area.

Summary: The book compiles efficient design and test methodologies for the implementation of reversible logic circuits. The methodologies covered in the book are design approaches, test approaches, fault tolerance in reversible circuits and physical implementation techniques. The book also covers the challenges and the reversible logic circuits to meet these challenges stimulated during each stage of work cycle. The novel computing paradigms are being explored to serve as a basis for fast and low power computation.

Summary: "The second edition of Digital and Social Media Marketing is an up to date, industry-led results-driven guide to digital marketing. Mixing academic theory with practical examples from a range of different organisations worldwide, it provides insight into, and techniques to enable, the creation, development and maintenance of a successful digital presence. This highly regarded textbook has been fully revised to bring the content up to date with the newest digital technologies. With topics including developing an effective digital presence, search engine optimization, and measuring brand awareness, the new edition also looks at digital ethics, General Data Protection Regulation (GDPR) and privacy, Artificial Intelligence (AI) and Machine Learning, and Voice strategies. New international case studies are explored, including Alibaba and Amazon, as well as revised practical exercises in each chapter, enable students to see how the concepts underpinning digital and social media marketing support business success. The book's customisable Digital Business Maturity Model, and the Buyer Persona Spring, offer organisations a clear roadmap for understanding their own levels of technology adoption and digital strategy development. This accessible textbook provides a hands-on, user-friendly platform to turn skills and knowledge into strategic advantage. It is ideal for advanced undergraduate and postgraduate students of digital marketing and marketing strategy, and for practitioners aiming to be at the cutting edge of Digital and Social Media Marketing. Alongside electronic resources for each chapter, this new edition also includes digital learning materials, case studies and exercises available in a supporting online learning environment. The online materials further enhance learners' experience and supports a worldwide learning community"-- Provided by publisher.

Summary: Tania Lewis offers the first critical account of the impact of digital information, media, and communication technologies on the topic of food. Lewis critically analyzes how our relationship to food consumption, production, and politics is being re-mediated through digitally connected electronic devices, practices and content. By drawing together the world of food and the digital, the book speaks to a number of pressing contemporary themes including the tensions around digital engagement in increasingly commercialized spaces; the changing nature of politics in a social media context; the growing naturalization of digital devices and related practices of data monitoring; and the role and impact of digitization on social relations. At the forefront of critical new research, and written with a student readership in mind, this text is essential for scholars interested in media studies, cultural studies, food studies, and cultural geography.

Summary: ""The next generation of systems and practices in journalism will require knowledge beyond online editing techniques, aggregation, social media flow and assumptions about fake news. The profession may also want to aim for ethical practices in journalism to be embedded in algorithms for new systems. Engagement in an early design phase may also be useful for scoping reforms for online and social media legislation. However, these pursuits require higher levels of understanding about backend data and online systems, and development of formal vocabulary for journalism concepts and practices. This new domain knowledge should also be expressed in ontological models, informed by participatory approaches. Some problems to be addressed include editorial control issues and fair distribution of news stories and other challenges of data and online systems. Problematic issues should also include the lack of transparency in corporate data sharing arrangements. The semantic language for future systems for journalism will be distinctly different from the vocabulary and classifications used for online news tags. It will also need to distinguish the vocabulary for social media things in context of journalism. Most importantly, the design of new systems will need participatory and semantic design methods that can support the need for high-level knowledge of data and semantic search methods. The influence of social media partnerships in news and backend data sharing are other problem areas. Data via integrated media systems in news organisations flows onto cloud servers where it is processed with a myriad of methods. These hubs are for the new generation of data sharing, where large volumes of data are sorted and processed at accelerated speeds, for a range of purposes. Cloud servers are now literally the highest levels of digital convergence, other than legislation, and the latter is lagging. This is where data is shared for advertising, social media benefits and other domain purposes. Integrated media systems bring benefits for global networked news media organisations, but they also enable more monetisation of data via cloud servers. ""-- Provided by publisher.

Summary: Use ensemble learning techniques and models to improve your machine learning results. Ensemble Learning for AI Developers starts you at the beginning with an historical overview and explains key ensemble techniques and why they are needed. You then will learn how to change training data using bagging, bootstrap aggregating, random forest models, and cross-validation methods. Authors Kumar and Jain provide best practices to guide you in combining models and using tools to boost performance of your machine learning projects. They teach you how to effectively implement ensemble concepts such as stacking and boosting and to utilize popular libraries such as Keras, Scikit Learn, TensorFlow, PyTorch, and Microsoft LightGBM. Tips are presented to apply ensemble learning in different data science problems, including time series data, imaging data, and NLP. Recent advances in ensemble learning are discussed. Sample code is provided in the form of scripts and the IPython notebook. You will: Understand the techniques and methods utilized in ensemble learning Use bagging, stacking, and boosting to improve performance of your machine learning projects by combining models to decrease variance, improve predictions, and reduce bias Enhance your machine learning architecture with ensemble learning.

Summary: Transform your IT organization from one weighed down by set practices to one with a DevOps culture and a cloud-first strategy that is optimized by automation and other lean practices. In this engaging read, you will discover the opportunities, challenges, lessons, and rewards that CA Technologies encountered when making their agile and DevOps transformation. In Enterprise DevOps Framework author Shamayel Farooqui shows you how agile adoption will enable your organization to stay ahead in an ever-changing business environment and meet your customers' needs. He includes detailed references to key concepts such as agile, hybrid and cloud technology, infrastructure management, and process automation. What You'll Learn: Establish the focus areas for your IT organization Prepare for the challenges of transforming your enterprise to a DevOps, agile organization Know the key steps for executing an enterprise DevOps strategy Build a strong team of DevOps individuals focused on improving the efficiency of your organization through Agile methodologies, automation, cloud adoption, and "infrastructure as code" practices

Summary: This book provides an in-depth analysis of the current evolutionary machine learning techniques. Discussing the most highly regarded methods for classification, clustering, regression, and prediction, it includes techniques such as support vector machines, extreme learning machines, evolutionary feature selection, artificial neural networks including feed-forward neural networks, multi-layer perceptron, probabilistic neural networks, self-optimizing neural networks, radial basis function networks, recurrent neural networks, spiking neural networks, neuro-fuzzy networks, modular neural networks, physical neural networks, and deep neural networks. The book provides essential definitions, literature reviews, and the training algorithms for machine learning using classical and modern nature-inspired techniques. It also investigates the pros and cons of classical training algorithms. It features a range of proven and recent nature-inspired algorithms used to train different types of artificial neural networks, including genetic algorithm, ant colony optimization, particle swarm optimization, grey wolf optimizer, whale optimization algorithm, ant lion optimizer, moth flame algorithm, dragonfly algorithm, salp swarm algorithm, multi-verse optimizer, and sine cosine algorithm. The book also covers applications of the improved artificial neural networks to solve classification, clustering, prediction and regression problems in diverse fields.