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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: This book presents the complex topic of using computational intelligence for pattern recognition in a straightforward and applicable way, using Matlab to illustrate topics and concepts. The author covers computational intelligence tools like particle swarm optimization, bacterial foraging, simulated annealing, genetic algorithm, and artificial neural networks. The Matlab based illustrations along with the code are given for every topic. Readers get a quick basic understanding of various pattern recognition techniques using only the required depth in math. The Matlab program and algorithm are given along with the running text, providing clarity and usefulness of the various techniques. Presents pattern recognition and the computational intelligence using Matlab; Includes mixtures of theory, math, and algorithms, letting readers understand the concepts quickly; Outlines an array of classifiers, various regression models, statistical tests and the techniques for pattern recognition using computational intelligence.

Summary: "First released in 1987, Near Dark is a vampire film set in the contemporary American Midwest that tells the story of Caleb, a half-vampire trying to decide whether to embrace his vampire nature or return to his human family. The film, an early work of the now-established director Kathryn Bigelow, skilfully mixes genre conventions, combining gothic tropes with those of the Western, road movie and film noir, while also introducing elements of the outlaw romance genre. Stacey Abbott's study of the film addresses it as a genre hybrid that also challenges conventions of the vampire film. The family of vampires who lure Caleb into their nocturnal existence is a central element of the film's innovative power: defined by a nomadic lifestyle, anarchic behaviour, a passion for violence, ambition for eternity, intense family bonds, and a gritty visual appearance. The vampires are morally ambiguous and undermine the class structures that have historically defined stories of the undead. These are not aristocrats but instead they capture the allure and horror of the disenfranchised and the underclass. The film is sumptuous in its aesthetic design, offering a nuanced and haunting presentation of its monstrous protagonists who stalk the Midwestern backroads and desert landscape. While it remains Bigelow's only foray into horror to date, its innovation showcases the creativity and artistic richness of the genre without sacrificing its visceral qualities. As Abbott describes, Near Dark was crucial in consolidating Bigelow's standing as a director of significance at an early point in her career, not simply because of her visual art background, but because of the way in which she would from Near Dark onward re-envision other traditionally mainstream genres of filmmaking"-- Provided by publisher.

Summary: "This book describes Machine Learning techniques and algorithms that have been used in recent real-world application. It provides an introduction to Machine Learning, describes the most widely used techniques and methods. It also covers Deep Learning and related areas such as function approximation or. The book gives real world examples where Machine Learning techniques are applied and describes the basic math and the commonly used learning techniques"-- Provided by publisher.

Summary: This book takes an in-depth look at the emerging technologies that are transforming the way clinicians manage patients, while at the same time emphasizing that the best practitioners use both artificial and human intelligence to make decisions. AI and machine learning are explored at length, with plain clinical English explanations of convolutional neural networks, back propagation, and digital image analysis. Real-world examples of how these tools are being employed are also discussed, including their value in diagnosing diabetic retinopathy, melanoma, breast cancer, cancer metastasis, and colorectal cancer, as well as in managing severe sepsis. With all the enthusiasm about AI and machine learning, it was also necessary to outline some of criticisms, obstacles, and limitations of these new tools. Among the criticisms discussed: the relative lack of hard scientific evidence supporting some of the latest algorithms and the so-called black box problem. A chapter on data analytics takes a deep dive into new ways to conduct subgroup analysis and how it's forcing healthcare executives to rethink the way they apply the results of large clinical trials to everyday medical practice. This re-evaluation is slowly affecting the way diabetes, heart disease, hypertension, and cancer are treated. The research discussed also suggests that data analytics will impact emergency medicine, medication management, and healthcare costs. An examination of the diagnostic reasoning process itself looks at how diagnostic errors are measured, what technological and cognitive errors are to blame, and what solutions are most likely to improve the process. It explores Type 1 and Type 2 reasoning methods; cognitive mistakes like availability bias, affective bias, and anchoring; and potential solutions such as the Human Diagnosis Project. Finally, the book explores the role of systems biology and precision medicine in clinical decision support and provides several case studies of how next generation AI is transforming patient care.

Summary: This book presents a unique approach to stream data mining. Unlike the vast majority of previous approaches, which are largely based on heuristics, it highlights methods and algorithms that are mathematically justified. First, it describes how to adapt static decision trees to accommodate data streams; in this regard, new splitting criteria are developed to guarantee that they are asymptotically equivalent to the classical batch tree. Moreover, new decision trees are designed, leading to the original concept of hybrid trees. In turn, nonparametric techniques based on Parzen kernels and orthogonal series are employed to address concept drift in the problem of non-stationary regressions and classification in a time-varying environment. Lastly, an extremely challenging problem that involves designing ensembles and automatically choosing their sizes is described and solved. Given its scope, the book is intended for a professional audience of researchers and practitioners who deal with stream data, e.g. in telecommunication, banking, and sensor networks.

Summary: "Sponsorship of sports, arts or events can be a powerful form of marketing communication for businesses and organizations. This new edition of Sponsorship in Marketing introduces the fundamentals of sponsorship-linked marketing, helping the reader to understand how sponsorship can be planned, executed and measured. Drawing on original research, and exploring key theory, best practice and cutting-edge issues, the book fully explains how the sponsor can implement successful sponsorship to achieve communication and engagement objectives. It covers every important conceptual and functional area of sponsorship in marketing communications, including: understanding the technology-led transformation of sponsoring audiences, strategies and objectives leveraging and activation in traditional and social media building sponsorship portfolios and rosters managing and ending relationships public policy and legal issues Every chapter includes international case studies and examples, test questions, and data from real organizations, business, campaigns and events, vividly illustrating the link between fundamental principles and effective practice. This updated edition features a new model of the sponsorship process with an ecosystem perspective, discussion of endorsers and influencers in sponsorship, an introduction to the impact of streaming on sponsoring, and entirely new thinking on sponsorship returns and evaluation. No other book provides such a comprehensive, evidence-based introduction to sponsorship, demonstrating how organizations can connect brands to real life. This is essential reading for all students and practitioners working in sport marketing, sport business, events marketing, arts administration, business communication or marketing management"-- Provided by publisher.

Summary: "This updated third edition presents a wide-scale, interdisciplinary guide to social media. Examining platforms like Facebook, Instagram, LinkedIn, Snapchat, TikTok, Twitter and YouTube, the book analyzes social media's use in journalism, broadcasting, public relations, advertising and marketing. Lipschultz focuses on key concepts, best practices, data analyses, law and ethics - all promoting the critical thinking that is needed to use new, evolving and maturing networking tools effectively within social and mobile media spaces. Featuring historical markers and contemporary case studies, essays from some of the industry's leading social media innovators and a comprehensive glossary, this practical, multipurpose textbook gives readers the resources they will need to both evaluate and utilize current and future forms of social media communication. Among other changes, updates to the third edition include a deep dive into new approaches to analytics, as well as greater discussion of law and ethics in light of the Facebook Cambridge Analytica scandal, the roll-out of GDPR and new case law relating to social media. Social Media Communication is the perfect social media primer for students and professionals, and, with a dedicated teaching guide, ideal for instructors, too"-- Provided by publisher.

Summary: "Netflix cofounder Reed Hastings reveals for the first time the unorthodox culture behind one of the world's most innovative, imaginative, and successful companies. There's never before been a company like Netflix. Not only because it has led a revolution in the entertainment industries; or because it generates billions of dollars in annual revenue; or even because it is watched by hundreds of millions of people in nearly 200 countries. When Reed Hastings co-founded Netflix, he developed a set of counterintuitive and radical management principles, defying all tradition and expectation, which would allow the company to reinvent itself over and over on the way to becoming one of the most loved brands in the world. Rejecting the conventional wisdom under which other companies operate, Reed set new standards, valuing people over process, emphasizing innovation over efficiency, and giving employees context, not controls. At Netflix, adequate performance gets a generous severance and hard work is irrelevant. At Netflix, you don't try to please your boss, you practice radical candor instead. At Netflix, employees never need approval, and the company always pays top of market. When Hastings and his team first devised these principles, the implications were unknown and untested, but over just a short period of time they have led to unprecedented flexibility, speed, and boldness. The culture of freedom and responsibility has allowed the company to constantly grow and change as the world, and its members' needs, have also transformed. Here for the first time, Hastings and Erin Meyer, bestselling author of The Culture Map and one of the world's most influential business thinkers, dive deep into the controversial philosophies at the heart of the Netflix psyche, which have generated results that are the envy of the business world. Drawing on hundreds of interviews with current and past Netflix employees from around the globe and never-before-told stories of trial and error from his own career, No Rules Rules is the full, fascinating, and untold story of a unique company making its mark on the world"-- Provided by publisher.

Summary: Everybody knows, and maybe even loves, a microgenre. Plague romances and mommy memoirs. Nudie-cutie movies, Nazi zombies, and dinosaur erotica. Baby burlesks, Minecraft fiction, grindcore, premature ejaculation poetry...microgenres come in all varieties and turn up in every form of media under the sun, tailor-made for enthusiasts of all walks of life. Coming into use in the last decade or so, the term "microgenre" classifies increasingly niche-marketed worlds in popular music, fiction, television, and the Internet. Netflix has recently highlighted our fascination with the ultra-niche genre with hilariously specific classifications -- “independent supernatural dramedy featuring a strong female lead” – that can sometimes hit a little too close to home. Each contribution in this collection introduces readers to a different microgenre, drawn from a range of historical periods and from a variety of media. The Microgenre presents a previously untreated point of cultural curiosity, revealing the profound truth that humanity's desire to classify is often only matched by the unsustainability of the obscure and hyper-specific. It also affirms, in colorful detail, what most people suspect but have trouble fathoming in an increasingly homogenized and commercial West: that imaginative projects are just that, imaginative, diverse, and sometimes completely and hilariously inexplicable.

Summary: "The fourth edition of Media and Entertainment Law has been fully updated, analysing some of the most recent judgments in media law from across the United Kingdom, such as: Cliff Richard v the BBC, Max Schrems v Facebook and the Irish Information Commissioner, developments on the 'right to be forgotten' (NT1 and NT2) and ABC v Daily Telegraph (Sir Philip Green). The book's two main themes are freedom of expression and an individual's right to privacy. Regulation of the communication industries is covered extensively, including discussion of the print press and its online editions following Leveson, traditional broadcasting regulations for terrestrial TV and radio as well as media activities on converged devices, such as tablets, iPads, mobile phone devices and 'on demand' services. Intellectual property law (specifically copyright) in the music and entertainment industries is also explored in the book's later chapters. Also new to this edition are sections on: A focus on freedom of expression: its philosophical foundations; the struggles of those who have fought for it; and the varied ways in which the courts interpret freedom of expression regarding the taking and publishing of photographs. The 'right to be forgotten', data breaches, and the General Data Protection Regulation (GDPR). The media's increasing access to the courts, particularly when considering the privacy of those who are suspected of sexual offences. Press regulators, broadcasting and advertising regulations, and film and video regulations. Election and party-political broadcast regulations, with a focus on social media and recent election fraud. The emergence of online music distribution services, internet radio and free digital streaming music services, and their effect on the music industry. The 4th edition also features a variety of pedagogical features to encourage critical analysis of case law and one's own beliefs"-- Provided by publisher.

Summary: Predictive Intelligence in Biomedical and Health Informatics focuses on imaging, computer-aided diagnosis and therapy as well as intelligent biomedical image processing and analysis. It develops computational models, methods and tools for biomedical engineering related to computer-aided diagnostics (CAD), computer-aided surgery (CAS), computational anatomy and bioinformatics. Large volumes of complex data are often a key feature of biomedical and engineering problems and computational intelligence helps to address such problems. Practical and validated solutions to hard biomedical and engineering problems can be developed by the applications of neural networks, support vector machines, reservoir computing, evolutionary optimization, biosignal processing, pattern recognition methods and other techniques to address complex problems of the real world.

Summary: This new edited volume consists of a collection of original articles written by leading financial economists and industry experts in the area of ​​machine learning for asset management. The chapters introduce the reader to some of the latest research developments in the area of ​​equity, multi-asset and factor investing. Each chapter deals with new methods for return and risk forecasting, stock selection, portfolio construction, performance attribution and transaction costs modeling. This volume will be of great help to portfolio managers, asset owners and consultants, as well as academics and students who want to improve their knowledge of machine learning in asset management.

Summary: Smart Card Security: Applications, Attacks, and Countermeasures provides an overview of smart card technology and explores different security attacks and countermeasures associated with it. It covers the origin of smart cards, types of smart cards, and how they work. It discusses security attacks associated with hardware, software, data, and users that are a part of smart card-based systems. The book starts with an introduction to the concept of smart cards and continues with a discussion of the different types of smart cards in use today, including various aspects regarding their configuration, underlying operating system, and usage. It then discusses different hardware- and software-level security attacks in smart card-based systems and applications and the appropriate countermeasures for these security attacks. It then investigates the security attacks on confidentiality, integrity, and availability of data in smart card-based systems and applications, including unauthorized remote monitoring, communication protocol exploitation, denial of service (DoS) attacks, and so forth, and presents the possible countermeasures for these attacks. The book continues with a focus on the security attacks against remote user authentication mechanisms in smart card-based applications and proposes a possible countermeasure for these attacks. Then it covers different communication standards for smart card-based applications and discusses the role of smart cards in various application areas as well as various open-source tools for the development and maintenance of smart card-based systems and applications. The final chapter explains the role of blockchain technology for securing smart card-based transactions and quantum cryptography for designing secure smart card-based algorithms. Smart Card Security: Applications, Attacks, and Countermeasures provides you with a broad overview of smart card technology and its various applications

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: "Amy Sargeant's compelling and meticulous study of Joseph Losey's The Servant (1963) sets the film in the context of a long tradition of fictional depictions of the master-servant relationship, from Shakespeare to Cervantes, Henry James, Dorothy L. Sayers and P.G. Wodehouse. Sargeant points out that while many of these relationships are played for comic effect, that of the 'young master' Tony (James Fox) and his manservant Barrett (Dirk Bogarde) unfolds in a far more sinister manner, with Barrett coming to dominate and humiliate the hapless Tony. Sargeant's reading pays particular attention to the contribution not only of Losey and Harold Pinter, who adapted the screenplay from Robin Maugham's novella, but also of the cinematographer Douglas Slocombe, designer Richard Macdonald and costume designer Beatrice 'Bumble' Dawson. She analyses the performances of Sarah Miles as Barrett's lover Vera and Wendy Craig as Tony's fiancee Susan, as well as those of Fox and Bogarde, and gives careful consideration to how the film uses architectural form, interior design and decoration, and clothing to establish character and relationships. In the context of the collapse of the British Empire, and a beleaguered Establishment beset by spy and sex scandals, the film can be read, Sargeant argues, as a metaphor for the 'state of the nation' in the early 1960s. Finally, Sargeant considers the film's critical and commercial reception in Britain, Europe and the United States - its release, how it was received as one of a number of 'emigre' films, and Losey's surprising denial of a homoerotic intent in the Tony-Barrett relationship. In her new foreword to this edition, Amy Sargeant considers contemporary resonances of the film's depiction of a twisted master-servant relationship in recent TV and cinema including The Crown, Downton Abbey and The Trial of Christine Keeler"-- Provided by publisher.

Summary: "This book lays a new foundation toward achieving artificial self-intelligence by future machines such as intelligent vehicles. Its chapters provide a broad coverage to the three key modules behind the design and development of intelligent vehicles for the ultimate purpose of actively ensuring driving safety as well as preventing accidents from all possible causes. Self-contained and unified in presentation, the book explains in details the fundamental solutions of vehicle's perception, vehicle's decision-making, and vehicle's action-taking in a pedagogic order. Besides the fundamental knowledge and concepts of intelligent vehicle's perception, decision and action, this book includes a comprehensive set of real-life application scenarios in which intelligent vehicles will play a major role or contribution. These case studies of real-life applications will help motivate students to learn this exciting subject. With concise and simple explanations, and boasting a rich set of graphical illustrations, the book is an invaluable source for both undergraduate and postgraduate courses, on artificial intelligence, intelligent vehicle, and robotics, which are offered in automotive engineering, computer engineering, electronic engineering, and mechanical engineering. In addition, the book will help strengthen the knowledge and skills of young researchers who want to venture into the research and development of artificial self-intelligence for intelligent vehicles of the future"-- Provided by publisher.

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: "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: 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: AWS is constantly driving new innovations that empower data scientists to explore a variety of machine learning (ML) cloud services. This book is your comprehensive reference for learning and implementing advanced ML algorithms in AWS cloud. As you go through the chapters, you’ll gain insights into how these algorithms can be trained, tuned and deployed in AWS using Apache Spark on Elastic Map Reduce (EMR), SageMaker, and TensorFlow. While you focus on algorithms such as XGBoost, linear models, factorization machines, and deep nets, the book will also provide you with an overview of AWS as well as detailed practical applications that will help you solve real-world problems. Every practical application includes a series of companion notebooks with all the necessary code to run on AWS. In the next few chapters, you will learn to use SageMaker and EMR Notebooks to perform a range of tasks, right from smart analytics, and predictive modeling, through to sentiment analysis.

Summary: "Producing New and Digital Media is your essential guide to understanding new media, taking a deep dive into such topics as the cultural and social impacts of the web, the importance of digital literacy, and creating in an online environment. This cutting-edge text provides an introductory, hands-on approach to creating user-generated content, coding, cultivating an online brand, and storytelling in new and digital media. In showing you how to navigate the world of digital media and complete digital tasks, this book not only teaches you how to use the web, but also helps you understand why you use it. Key features for the 2nd edition include: Coverage of up-to-date forms of communication on the web: memes, viral videos, social media, and more pervasive types of online languages. New chapters on YouTube influencers and on-demand subscription television. Each chapter has media literacy sidebars, sample assignments, and activities. Updates to the companion website additional materials for students and instructors Thoughtful, entertaining and enlightening, this is the fundamental textbook for students of new and digital media, digital culture and media literacy, as well as a useful resource for anyone wanting to understand and develop their presence in our digital world"-- Provided by publisher.

Summary: This book presents a cutting-edge research procedure in the Nature-Inspired Computing (NIC) domain and its connections with computational intelligence areas in real-world engineering applications. It introduces readers to a broad range of algorithms, such as genetic algorithms, particle swarm optimization, the firefly algorithm, flower pollination algorithm, collision-based optimization algorithm, bat algorithm, ant colony optimization, and multi-agent systems. In turn, it provides an overview of meta-heuristic algorithms, comparing the advantages and disadvantages of each. Moreover, the book provides a brief outline of the integration of nature-inspired computing techniques and various computational intelligence paradigms, and highlights nature-inspired computing techniques in a range of applications, including: evolutionary robotics, sports training planning, assessment of water distribution systems, flood simulation and forecasting, traffic control, gene expression analysis, antenna array design, and scheduling/dynamic resource management.

Summary: "The five-time Emmy Award-winning investigative reporter and New York Times bestselling author of Stonewalled and The Smear uncovers how partisan bias and gullibility are destroying American journalism"-- Provided by publisher.

Summary: Use popular data mining techniques in Microsoft Excel to better understand machine learning methods. Software tools and programming language packages take data input and deliver data mining results directly, presenting no insight on working mechanics and creating a chasm between input and output. This is where Excel can help. Excel allows you to work with data in a transparent manner. When you open an Excel file, data is visible immediately and you can work with it directly. Intermediate results can be examined while you are conducting your mining task, offering a deeper understanding of how data is manipulated and results are obtained. These are critical aspects of the model construction process that are hidden in software tools and programming language packages. This book teaches you data mining through Excel. You will learn how Excel has an advantage in data mining when the data sets are not too large. It can give you a visual representation of data mining, building confidence in your results. You will go through every step manually, which offers not only an active learning experience, but teaches you how the mining process works and how to find the internal hidden patterns inside the data. What You Will Learn: Comprehend data mining using a visual step-by-step approach Build on a theoretical introduction of a data mining method, followed by an Excel implementation Unveil the mystery behind machine learning algorithms, making a complex topic accessible to everyone Become skilled in creative uses of Excel formulas and functions Obtain hands-on experience with data mining and Excel This book is for anyone who is interested in learning data mining or machine learning, especially data science visual learners and people skilled in Excel, who would like to explore data science topics and/or expand their Excel skills. A basic or beginner level understanding of Excel is recommended. Hong Zhou, PhD is a professor of computer science and mathematics and has been teaching c ourses in computer science, data science, mathematics, and informatics at the University of Saint Joseph for more than 15 years. His research interests include bioinformatics, data mining, software agents, and blockchain. Prior to his current position, he was as a Java developer in Silicon Valley. Dr. Zhou believes that learners can develop a better foundation of data mining models when they visually experience them step-by-step, which is what Excel offers. He has employed Excel in teaching data mining and finds it an effective approach for both data mining learners and educators.

Summary: "In this current period of uncertainty and introspection in the media, New Journalisms focuses not just on new challenges facing journalism, but also seeks to capture a wide range of new practices that are being employed across a diversity of media. This edited collection explores how these new practices can lead to a re-imagining of journalism in terms of practice, theory and pedagogy, bringing together high-profile academics, emerging researchers and well-known journalism practitioners. The book's opening chapters assess the challenges of loss of trust and connectivity, shifting professional identity and the demise of local journalism. A section on new practices evaluates algorithms, online participatory news websites and verification. Finally, the collection explores whether new pedagogies offer potential routes to new journalisms. Representing a timely intervention in the debate and providing sustainable impact through its forward-looking focus, New Journalisms is essential reading for students of journalism and media studies"-- Provided by publisher.

Summary: Saransh works at a life insurance company, as part of the Special Projects Group (SPG). Their current project is top-secret: the development of an Artificial Intelligence system that will leave 552 branch-level employees redundant overnight. Because of site-specific customizations, however, the system needs to collect information from the company's various branches. Thus, begins a cycle in which Saransh travels across the country, interviewing the very people that his machine will replace soon. Meanwhile, his conscientious ex-journalist girlfriend Jyoti repeatedly questions Saransh's complicity in the impending destruction of hundreds of lives. The Machine is Learning is a novel about twenty-first-century workplaces, love and the impact of technology in all of our lives. It interrogates a world order that accommodates guilt but offers no truly ethical course correction.

Summary: A hands-on, readable guide to machine learning with R. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to uncover key insights and make new predictions. The 3rd edition features newer and better libraries, advice on ethical and bias issues, and an introduction to deep learning.

Summary: "This book is a collection of research on the advancement of intelligent technology in industrial environments and its applications within the manufacturing field"-- Provided by publisher.

Summary: This book covers the different technologies of Internet, and machine learning capabilities involved in Cognitive Internet of Things (CIoT). Machine learning is explored by covering all the technical issues and various models used for data analytics during decision making at different steps. It initiates with IoT basics, its history, architecture and applications followed by capabilities of CIoT in real world and description of machine learning (ML) in data mining. Further, it explains various ML techniques and paradigms with different phases of data pre-processing and feature engineering. Each chapter includes sample questions to help understand concepts of ML used in different applications. Explains integration of Machine Learning in IoT for building an efficient decision support system Covers IoT, CIoT, machine learning paradigms and models Includes implementation of machine learning models in R Help the analysts and developers to work efficiently with emerging technologies such as data analytics, data processing, Big Data, Robotics Includes programming codes in Python/Matlab/R alongwith practical examples, questions and multiple choice questions

Summary: In this revised and expanded edition of Predictably Irrational, Dan Ariely explores the hidden forces that shape our decisions, including some of the causes responsible for the current economic crisis. Bringing a much-needed dose of sophisticated psychological study to the realm of public policy, Ariely offers his own insights into the irrationalities of everyday life, the decisions that led us to the financial meltdown of 2008, and the general ways we get ourselves into trouble.

Summary: "Investigative Journalism, Democracy and the Digital Age explores watchdog reporting in the digital age. Mapping new forms of global collaborative investigative journalism, the book debunks the myth that traditional newsrooms and investigative journalism are dying, and shows how journalists are adapting and experimenting. The book brings together expert analysis and lively examples of investigative journalism in developed economies, with a close focus on the United States, United Kingdom and Australia. Combining decades of investigative journalism analyses with expert interviews with watchdog reporters from across the globe, the author shows us how investigative journalism thrives despite significant challenges, and explores why investigative journalism is integral to democratic accountability and public trust in the news in a fake news era"-- Provided by publisher.

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.

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: 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: 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: This unique book discusses a selection of highly relevant topics in the Social Internet of Things (SIoT), including blockchain, fog computing and data fusion. It also presents numerous SIoT-related applications in fields such as agriculture, health care, education and security, allowing researchers and industry practitioners to gain a better understanding of the Social Internet of Things.

Summary: Learn how to apply the principles of machine learning to time series modeling with this indispensable resource Machine Learning for Time Series Forecasting with Python is an incisive and straightforward examination of one of the most crucial elements of decision-making in finance, marketing, education, and healthcare: time series modeling. Despite the centrality of time series forecasting, few business analysts are familiar with the power or utility of applying machine learning to time series modeling. Author Francesca Lazzeri, a distinguished machine learning scientist and economist, corrects that deficiency by providing readers with comprehensive and approachable explanation and treatment of the application of machine learning to time series forecasting. Written for readers who have little to no experience in time series forecasting or machine learning, the book comprehensively covers all the topics necessary to: Understand time series forecasting concepts, such as stationarity, horizon, trend, and seasonality Prepare time series data for modeling Evaluate time series forecasting models' performance and accuracy Understand when to use neural networks instead of traditional time series models in time series forecasting Machine Learning for Time Series Forecasting with Python is full real-world examples, resources and concrete strategies to help readers explore and transform data and develop usable, practical time series forecasts. Perfect for entry-level data scientists, business analysts, developers, and researchers, this book is an invaluable and indispensable guide to the fundamental and advanced concepts of machine learning applied to time series modeling.

Summary: Formal Methods in Computer Science gives students a comprehensive introduction to formal methods and their application in software and hardware specification and verification. The first part introduces some fundamentals in formal methods, including set theory, functions, finite state machines, and regular expressions. The second part focuses on logic, a powerful formal language in specifying systems properties. It covers propositional logic, predicate logic, temporal logic, and model checking. The third part presents Petri nets, the most popular formal language in system behavior modeling. In additional to regular Petri nets, this part also examines timed Petri nets and high-level Petri nets. The textbook is ideal for undergraduate or graduate courses in computer engineering, software engineering, computer science, and information technology programs. Parts of the book are useful reading material in undergraduate computer course and as a reference guide for students researching the area of formal system specification and validation.

Summary: "The recipient of multiple Peabody and Murrow awards, Clarissa Ward is a world-renowned conflict reporter. In this strange age of crisis where there really is no front line, she has moved from one hot zone to the next. With multiple assignments in Syria, Egypt, and Afghanistan, Ward, who speaks seven languages, has been based in Baghdad, Beirut, Beijing, and Moscow. She has seen and documented the violent remaking of the world at close range. With her deep empathy, Ward finds a way to tell the hardest stories. On All Fronts is the riveting account of Ward's singular career and of journalism in this age of extremism. Following a privileged but lonely childhood, Ward found her calling as an international war correspondent in the aftermath of 9/11. From her early days in the field, she was embedding with marines at the height of the Iraq War and was soon on assignment all over the globe. But nowhere does Ward make her mark more than in war-torn Syria, which she has covered extensively with courage and compassion. From her multiple stints entrenched with Syrian rebels to her deep investigations into the Western extremists who are drawn to ISIS, Ward has covered Bashar al-Assad's reign of terror without fear. In 2018, Ward rose to new heights at CNN and had a son. Suddenly, she was doing this hardest of jobs with a whole new perspective"-- Provided by publisher.

Summary: "Examines U.S. metro dailies, the newspapers hit hardest by declines in advertising and circulation, and how they continue to survive and contribute important news coverage despite predictions that they would eventually wither away"-- Provided by publisher.

Summary: "The book introduces probabilistic machine learning concepts to civil engineering students and professionals, who typically do not have the background necessary to understand the subject from a purely computer science perspective. It presents key approaches among the three sub-fields of machine learning: supervised, unsupervised, and reinforcement learning. The methods are demonstrated through step-by-step examples and copius illustrations in order to simplify abstract concepts. The book will prepare readers to access the vast body of literature from the field of machine learning"-- 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.