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Summary: "This book offers high-quality original research contributions on the specialized theme of cybersecurity challenges in diverse business areas, disseminating theoretical foundations and empirical studies by researchers and practitioners to realize dependable technological systems"-- Provided by publisher.

Summary: "This handbook is a comprehensive study of the archaeology, social history, and the cultural landscape of the Hindu temple. Perhaps the most recognizable of the material forms of Hinduism, temples are lived, dynamic spaces that are significant sites of the creation of cultural heritage, both in the past and the present. Drawing on historiographical surveys and in-depth case studies, the volume centres the material form of the Hindu temple as an entry point to study its many adaptations and transformations from the early centuries CE to the 20th century. It highlights the vibrancy and dynamism of the shrine in different locales and studies the active participation of the community for its establishment, maintenance, and survival. The illustrated handbook takes a unique approach by focusing on the social base of the temple rather than its aesthetics or chronological linear development. It fills a significant gap in the study of Hinduism and will be an indispensable resource for scholars of archaeology, Hinduism, Indian history, religious studies, museum studies, South Asian history, and Southeast Asian history"-- Provided by publisher.

Summary: "This book presents the advances in AI-assisted agile IoT for fintech, helping readers to reveal new applications, current issues, challenges and future directions in the field of AI-assisted agile IoT for fintech applications and ecosystems"-- Provided by publisher.

Summary: "This new volume, Empowering Artificial Intelligence Through Machine Learning: New Advances and Applications, discusses various new applications of machine learning, a subset of the field of artificial intelligence. Artificial intelligence is considered to be the next big-game changer in research and technology. The volume looks at how computing has enabled machines to learn, making machines and tools become smarter in many sectors, including science and engineering, healthcare, finance, education, gaming, security, and even agriculture, plus many more areas. Topics include techniques and methods in artificial intelligence for making machines intelligent, machine learning in healthcare, using machine learning for credit card fraud detection, using artificial intelligence in education using gaming and automatization with courses and outcomes mapping, and much more. The book will be valuable for professionals, faculty, and students in electronics and communication engineering, telecommunication engineering, network engineering, computer science and information technology"-- Provided by publisher.

Summary: "This book guides monetary authority on CBDC policy choices, improve upon CBDC interoperability and minimize implementation challenges overrun. Covering topics such as the digital euro, ethical implications, and sustainable development goals, this book is an essential resource for banks, high frequency traders, insurance companies, and finance professionals as they position themselves to leverage on CBDC and Fintech applications"-- Provided by publisher.

Summary: "Fintech, the integration of technology into the delivery of financial services has revolutionised the world of Finance. This book introduces a new framework to study the concepts that underly Fintech while examining the driving forces and underlying logic behind Fintech-based innovation and predicting the future development of Fintech. The first three parts of the book cover the development and basics of Fintech and its relationship with inclusive finance, while later sections constitute a deep dive into several core issues surrounding Fintech. First, the volume introduces an economic explanation of blockchain and its application in various scenarios based on the token paradigm. Second, it studies digital currency and discusses its impacts on payment systems, financial inclusion, monetary policy, and financial stability. Third, the authors explore how to build a compliant and effective market for data while protecting data privacy, impinging on the future development of AI application, the digital economy and Fintech. Fourth, the book examines public policies related to Fintech, including regulatory technology, the regulation of financial activities of Big Tech companies, and how to promote financial inclusion. The title will appeal to scholars, students, and financial practitioners and regulators in a broad range of areas including economics, finance, technology, and public policy, especially Fintech, blockchain, and digital currency"-- Provided by publisher.

Summary: "This book highlights how FinTech supports the availability and equality of opportunities to access financial services for individuals and businesses to take advantage of affordable, and timely financial products and services by featuring conceptual, case studies, recent development, best practices, comparative assessment, business processes, as well as strategies and outputs in studies of FinTech from multiple domains of knowledge"-- Provided by publisher.

Summary: "Health Economics and Financing is a primer for the economic analysis of medical markets. Its intended audiences are students of medicine, public health, policy, and administration who wish to engage the central economic issues of their field without prolonged preparatory work; beginning students in economics who wish to study an applied area in detail without recourse to extensive mathematical manipulation; and more advanced students in economics who may be familiar with analytical techniques but lack knowledge of the many institutional features that make the study of health and health care so unique and rewarding. This book draws upon the work of many scholars, but in keeping with its design as a primer for introducing students to the principles and concepts of health economics rather than its literature and research methods, the use of attribution, footnotes, and references is purposely limited. Suggestions for additional reading and more advanced source materials and databases are listed at the end of each chapter and are available on the instructor's website at www.wiley.com/go/getzen/healtheconomics6e. The first eleven chapters use a flow-of-funds approach to investigate the sources and uses of financing and to explore the incentives and organizational structure of the health care system. Transactions between patients and physicians (and others) are examined to see how profits are made, costs covered, contracts written (or implied), and regulations formed. The long-term consequences of exchanging services for money in a particular way are revealed by exploring the historical development of those distinctive features that characterize the industrial organization of health care: licensure, third-party insurance, nonprofit hospitals, and government regulation. The last five chapters take a wider macroeconomic perspective in order to explore the dynamics of change within the health care system and to explicitly consider determinants of national health spending and the role of governments in public and private health"-- Provided by publisher.

Summary: "This book breaks new ground by examining trans-oceanic connectivity through the perspective of coastal shrines and maritime cultural landscapes across the Bay of Bengal and the South China Sea. It covers a period of expanding networks and cross-cultural encounters from the 3rd century BCE to the 13th century CE. The book examines the distinctiveness of these shrines, and highlights their interconnections, and their role in social integration in South and Southeast Asia. By drawing on data from shipwreck sites, the author elaborates on the material and religious intersections and transmissions between cultures across the seas. Many of these coastal shrines survived into the colonial period when they came to be admired for their aesthetic value as 'monuments'. As nation states of the region became independent, these shrines were often inscribed on UNESCO's World Heritage List on account of their Outstanding Universal Values. The book argues that in the 21st century there is a need to promote the cultural connectivity of the past as transnational heritage on UNESCO's global platform to preserve and protect our shared heritage. The volume will be essential reading for academics and researchers of archaeology, anthropology, museum and heritage studies, history of South and Southeast Asia, religious studies, cultural studies, and Asian studies"-- Provided by publisher.

Summary: Introduction to cognitive computing and its various applications Recent trends towards cognitive science: from robots to humanized robots Cognitive compyuting in human activity recognition by healthcare robots Deep learning-based cognitive state prediction analysis using brain wave signals EEG-based cognitive performance evaluations for mental arithmetic tasks Trust or no trust in chat-bots: a millennial dilemma Cognitive computing in autonomous vehicles Optimized navigation using deep learning techniques for automatic guided vehicles Vehicular middleware and heuristic approaches for ITS systems of smart cities Error traceability and error prediction using machine learning techniques to improve the quality of vehicle modeling in computer-aided engineering All about human-robot interaction Teleportation of human body kinematicss for a tangible humanoid robot control Recognition of trivial humanoid group events using clustering and higher order local auto-correlation techniques Understanding the hand gesture command to visual attention model for mobile robot navigation: service robots in the domestic environment Mobile robots for air quality monitoring of landfill sites using the Internet of Things Artificial intelligence and Internet of Things readiness: the inclination for hotels to support a sustainable envoronment Design and fabrication of a new multi-function smart trash bin based on the Internet of Things

Summary: "In Digital Finance: Security Tokens and Unlocking the Real Potential Blockchain, readers will realize why security tokens are creating huge excitement in the financial industry. By combining the latest in technology and the potential for automated world-class investor protections, regulatory compliance and customer service, security tokens offer a plethora of benefits that will drive cost reductions, enhance flexibility and open up opportunities for new business models and revenue streams. Digital Finance thoroughly examines how this powerful technology can overhaul our current financial infrastructure in a way that will increase efficiency, transparency, and security"-- Provided by publisher.

Summary: "Every day we make choices--about food and other purchases, financial investments, our children's health and education, even the causes we champion or the planet itself. Unfortunately, we often choose poorly. Using dozens of eye-opening examples and drawing on decades of behavioral science research, Nudge shows how sensible "choice architecture" can help us to overcome the biases that lead to bad decisions and nudge us toward the best decisions for ourselves, our families, and our society"-- Provided by publisher.

Summary: "A timely new edition of the classic journalism guide, now featuring updated material on the importance of reporting in the age of media mistrust and fake news--and how journalists can use technology while also navigating its challenges. More than two decades ago, the Committee of Concerned Journalists gathered some of America's most influential newspeople to ask the question "What is journalism for?" Through exhaustive research, surveys, interviews, and public forums, they identified the essential elements that define journalism and its role in our society. The result is one of the most important books on the media ever written, winner of the Goldsmith Book Prize from Harvard, the Society of Professional Journalists Award, and the Bart Richards Award from Penn State University. Updated with new material covering the ways journalists can deftly leverage technology to their advantage, especially given the shifting revenue architecture--with "clickbait" fading away and consumers paying a higher premium for quality reporting--this fourth edition of The Elements of Journalism is an essential read for journalists, students, and anybody hoping to stay informed in contentious times"-- Provided by publisher.

Summary: "This book discusses the relationship between media, conflict and democratisation in Africa from the perspective of media ethics. Despite the commonly held view that conflict is a destructive political force that can destabilize democracies, the argument in this book is that while many conflicts can become violent and destructive, they can also be managed in a way that can render them productive and communicative to democracy. Drawing on theoretical insights from the fields of journalism studies, political studies and cultural studies, the book discusses the ethics of conflict coverage and proposes a normative model for covering conflict and democratisation. The book argues for an 'ethics of listening' which would enable the media to de-escalate violent conflict and contribute to the deepening of an agonistic democratic culture in contexts of high inequality, ethnic and racial polarisation and uneven access to media. This argument is illustrated by examples drawn from recent events in African democracies such as student protests, community activism, struggles for resources and social media conflicts. The book also scrutinizes the media's ethical roles and responsibilities in African societies by considering questions regarding journalistic professionalism, ethical codes and regulation in the context of rising misinformation. Provides a critical African perspective on global debates about media, politics, and democracy and the media's ethical commitments in contexts of conflict"-- Provided by publisher.

Summary: Delve into the world of reinforcement learning algorithms and apply them to different use-cases via Python. This book covers important topics such as policy gradients and Q learning, and utilizes frameworks such as Tensorflow, Keras, and OpenAI Gym. Applied Reinforcement Learning with Python introduces you to the theory behind reinforcement learning (RL) algorithms and the code that will be used to implement them. You will take a guided tour through features of OpenAI Gym, from utilizing standard libraries to creating your own environments, then discover how to frame reinforcement learning problems so you can research, develop, and deploy RL-based solutions. What You'll Learn: Implement reinforcement learning with Python Work with AI frameworks such as OpenAI Gym, Tensorflow, and Keras Deploy and train reinforcement learning–based solutions via cloud resources Apply practical applications of reinforcement learning.

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 provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data"-- Provided by publisher.

Summary: "The book begins by going over the basics of R and the tidyverse. You learn R throughout the book, but in the first part we go over the building blocks needed to keep learning during the rest of the book"-- Provided by publisher.

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: 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: "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: "The Routledge Handbook on Historic Urban Landscapes in Asia-Pacific sheds light onto the balancing act of urban heritage management, focusing specifically on the Asia-Pacific regions in which this challenge is imminent and in need of effective solutions. Urban heritage, while being threatened amidst myriad forces of global and ecological change, provides a vital social, cultural, and economic asset for regeneration and sustenance of liveability of inhabited urban areas worldwide. This six-part volume takes a critical look at the concept of Historic Urban Landscapes, the approach that UNESCO promotes to achieve holistic management of urban heritage, through the lens of issues, prospects, and experiences of urban regeneration of the selected geo-cultural context. It further discusses the difficult task that heritage managers encounter in conceptualizing, mapping, curating, and sustaining the plurality, poetics, and politics of urban heritage of the regions in question. The connective thesis that weaves the chapters in this volume together reinforces for readers that the management of urban heritage considers cities as dynamic entities, palimpsests of historical memories, collages of social diversity, territories of contested identities, and sites for sustainable liveability. Throughout this edited collection, chapters argue for recognizing the totality of the eco-cultural urban fabric, embracing change, building social cohesion, and initiating strategic socio-economic progress in the conservation of historic urban landscapes. Containing thirty-six contributions written by leading regional experts, and illustrated with over 200 black and white images and tables, this volume provides a much-needed resource on historic urban landscapes for students, scholars and researchers"-- Provided by publisher.

Summary: "Where Ideas Go to Die explores the troubled relationship of US journalism and intellect. A defender of common sense, the press is irked at intellect yet often dependent on its critical autonomy. A postwar observation from Richard Hofstadter applies to contemporary journalists: "Men do not rise in the morning, grin at themselves in their mirrors, and say: 'Ah, today I shall torment an intellectual and strangle an idea!'" The book nevertheless documents the prowess of news media in the policing of intellect. Control extends beyond suppression of ideas and ways of thinking to the aggressive rendering of dissent into deviance. The social control of intellect by journalism is accompanied by social control of journalism in newsrooms and in classrooms where norms are cultivated. Anti-intellectualism consequently operates like dark matter in media, a presence inferred by its effects rather than directly observed or acknowledged. When journalists anticipate a punitive public, the reified resentment is no more real than the fiction of omnipotent citizens in democratic theory, yet the audience imagined compels how intellect is rendered in the news as nuisance, deviance, or object of ridicule. Journalism's contribution to the social control of ideas is poignantly democratic: audiences are cast in consequential roles that affirm their wisdom in a closed, self-referential system. The book concludes with a discussion about what intellectual journalism would look like. Interviews with 25 "dangerous professors" demonstrate how alliances in the academic-media nexus can seed intellect in newswork"-- Provided by publisher.

Summary: "Meet the biggest animal on land--the African elephant! Everything about this title is big, from the full-bleed photographs to the content." -- Amazon.com.

Summary: "Amid the torrent of information we receive every day, aggregation of previously reported stories allows readers to streamline, summarize, and process the news. While aggregation in one form or another has been part of journalism since the nineteenth century, it has taken on a new prominence and influence in today's media ecosystem While aggregation practices are increasingly being adopted by new digital entities and leading news organizations via news apps, e-mail newsletters, and other formats, they are denigrated by journalists as not "real" journalism and inferior to reporting. More recently, aggregation has been viewed with suspicion as a practice that allows for the news to be repackaged in ways that reflect political bias. Despite the tendency of some aggregators to distort the news, whether for the purpose of clicks or politics, aggregation, Coddington argues, serve an important purpose in the contemporary news environment. Given that aggregation is likely here to stay, journalists and readers need to develop practices to better understand and improve its implementation and influence. Coddington's work is based on his fieldwork and interviews with aggregators at five different news organizations, including both startups and legacy media organizations that use aggregation. The book focuses on how aggregators make decisions on what to publish, how they create narrative, how they understand their audiences, and how they view their own work"-- Provided by publisher.

Summary: "Always Get the Name of the Dog is a guide to journalistic interviewing written by a journalist for journalists. It features advice from some of the best writers and reporters in the business and takes a comprehensive view of media interviewing across multiple platforms, while emphasizing active learning to give readers actionable steps to become great media interviewers. Through real scenarios and examples, this text takes future journalists through the steps of the interview, from research to source identification to question development and beyond. Whether you are a journalism student or an experienced reporter looking to sharpen your skills, this text can help make sure you get all you need from every interview you conduct"-- Provided by publisher.

Summary: The next big area within the information and communication technology field is Artificial Intelligence (AI). The industry is moving to automate networks, cloud-based systems (e.g., Salesforce), databases (e.g., Oracle), AWS machine learning (e.g., Amazon Lex), and creating infrastructure that has the ability to adapt in real-time to changes and learn what to anticipate in the future. It is an area of technology that is coming faster and penetrating more areas of business than any other in our history. AI will be used from the C-suite to the distribution warehouse floor. Replete with case studies, this book provides a working knowledge of AI's current and future capabilities and the impact it will have on every business. It covers everything from healthcare to warehousing, banking, finance and education. It is essential reading for anyone involved in industry.

Summary: Build your own chatbot using Python and open source tools. This book begins with an introduction to chatbots where you will gain vital information on their architecture. You will then dive straight into natural language processing with the natural language toolkit (NLTK) for building a custom language processing platform for your chatbot. With this foundation, you will take a look at different natural language processing techniques so that you can choose the right one for you. The next stage is to learn to build a chatbot using the API.ai platform and define its intents and entities. During this example, you will learn to enable communication with your bot and also take a look at key points of its integration and deployment. The final chapter of Building Chatbots with Python teaches you how to build, train, and deploy your very own chatbot. Using open source libraries and machine learning techniques you will learn to predict conditions for your bot and develop a conversational agent as a web application. Finally you will deploy your chatbot on your own server with AWS. You will: Gain the basics of natural language processing using Python Collect data and train your data for the chatbot Build your chatbot from scratch as a web app Integrate your chatbots with Facebook, Slack, and Telegram Deploy chatbots on your own server.

Summary: "Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Use machine learning to understand your customers, frame decisions, and drive value The business analytics world has changed, and Data Scientists are taking over. Business Data Science takes you through the steps of using machine learning to implement best-in-class business data science. Whether you are a business leader with a desire to go deep on data, or an engineer who wants to learn how to apply Machine Learning to business problems, you'll find the information, insight, and tools you need to flourish in today's data-driven economy. You'll learn how to: Use the key building blocks of Machine Learning: sparse regularization, out-of-sample validation, and latent factor and topic modeling. Understand how use ML tools in real world business problems, where causation matters more that correlation. data science programs by scripting in the R programming language Today's business landscape is driven by data and constantly shifting. Companies live and die on their ability to make and implement the right decisions quickly and effectively. Business Data Science is about doing data science right. It's about the exciting things being done around Big Data to run a flourishing business. It's about the precepts, principals, and best practices that you need know for best-in-class business data science"-- Provided by publisher.

Summary: Explore the theory and practical applications of artificial intelligence (AI) and machine learning in healthcare. This book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare and big data challenges. You'll discover the ethical implications of healthcare data analytics and the future of AI in population and patient health optimization. You'll also create a machine learning model, evaluate performance and operationalize its outcomes within your organization. Machine Learning and AI for Healthcare provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of AI applications. These are illustrated through leading case studies, including how chronic disease is being redefined through patient-led data learning and the Internet of Things.

Summary: Using the Pi Camera and a Raspberry Pi board, expand and replicate interesting machine learning (ML) experiments. This book provides a solid overview of ML and a myriad of underlying topics to further explore. Non-technical discussions temper complex technical explanations to make the hottest and most complex topic in the hobbyist world of computing understandable and approachable. Machine learning, also commonly referred to as deep learning (DL), is currently being integrated into a multitude of commercial products as well as widely being used in industrial, medical, and military applications. It is hard to find any modern human activity, which has not been "touched" by artificial intelligence (AI) applications. Building on the concepts first presented in Beginning Artificial Intelligence with the Raspberry Pi, you’ll go beyond simply understanding the concepts of AI into working with real machine learning experiments and applying practical deep learning concepts to experiments with the Pi board and computer vision. What you learn with Machine Learning with the Raspberry Pi can then be moved on to other platforms to go even further in the world of AI and ML to better your hobbyist or commercial projects.

Summary: "Now in its fourth edition, Media Effects again features essays from some of the finest scholars in the field and serves as a comprehensive reference volume for scholars, teachers, and students. This edition contains both new and updated content that reflects our media-saturated environments, including chapters on social media, video games, mobile communication, and virtual technologies. In recognition of the multitude of research trajectories within media effects, this edition also includes new chapters on narratives, positive media, the self and identity, media selection, and cross-cultural media effects. As scholarship in media effects continues to evolve and expand, Media Effects serves as a benchmark of theory and research for the current and future generations of scholars. Ideal for scholars and for undergraduate and graduate courses in media effects, media psychology, media theory, psychology, sociology, political science, and related disciplines"-- Provided by publisher.

Summary: This book focuses on mediated intercultural communication in the context of globalization. Analyzing social and traditional media using qualitative, interpretive, and critical and cultural perspectives, contributors engage with diverse topics - ranging from hybrid identities in different communities, to journalistic collaborations in the global media landscape. In addition, the authors also examine the placeless and borderless communities of diaspora members, their transnational identities, and the social media stories that shape and are shaped by them.

Summary: Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications illustrates recent advances in the field of mem-elements (memristor, memcapacitor, meminductor) and their applications in nonlinear dynamical systems, computer science, analog and digital systems, and in neuromorphic circuits and artificial intelligence. The book is mainly devoted to recent results, critical aspects and perspectives of ongoing research on relevant topics, all involving networks of mem-elements devices in diverse applications. Sections contribute to the discussion of memristive materials and transport mechanisms, presenting various types of physical structures that can be fabricated to realize mem-elements in integrated circuits and device modeling. As the last decade has seen an increasing interest in recent advances in mem-elements and their applications in neuromorphic circuits and artificial intelligence, this book will attract researchers in various fields.

Summary: Leverage Natural Language Processing (NLP) in Python and learn how to set up your own robust environment for performing text analytics. The second edition of this book will show you how to use the latest state-of-the-art frameworks in NLP, coupled with Machine Learning and Deep Learning to solve real-world case studies leveraging the power of Python. This edition has gone through a major revamp introducing several major changes and new topics based on the recent trends in NLP. We have a dedicated chapter around Python for NLP covering fundamentals on how to work with strings and text data along with introducing the current state-of-the-art open-source frameworks in NLP. We have a dedicated chapter on feature engineering representation methods for text data including both traditional statistical models and newer deep learning based embedding models. Techniques around parsing and processing text data have also been improved with some new methods. Considering popular NLP applications, for text classification, we also cover methods for tuning and improving our models. Text Summarization has gone through a major overhaul in the context of topic models where we showcase how to build, tune and interpret topic models in the context of an interest dataset on NIPS conference papers. Similarly, we cover text similarity techniques with a real-world example of movie recommenders. Sentiment Analysis is covered in-depth with both supervised and unsupervised techniques. We also cover both machine learning and deep learning models for supervised sentiment analysis. Semantic Analysis gets its own dedicated chapter where we also showcase how you can build your own Named Entity Recognition (NER) system from scratch. To conclude things, we also have a completely new chapter on the promised of Deep Learning for NLP where we also showcase a hands-on example on deep transfer learning. While the overall structure of the book remains the same, the entire code base, modules, and chapters will be updated to the latest Python 3.x release. ---------------------------------- Also the key selling points ? Implementations are based on Python 3.x and state-of-the-art popular open source libraries in NLP ? Covers Machine Learning and Deep Learning for Advanced Text Analytics and NLP ? Showcases diverse NLP applications including Classification, Clustering, Similarity Recommenders, Topic Models, Sentiment and Semantic Analysis.