English | 2022 | ISBN: 1803244887 | 314 pages | True PDF | 20.23 MB
Explore Ansible Automation Platform and understand how the different pieces interact to standardize and scale automation
Key Features

English | 2022 | ISBN: 0472133128 | 255 pages | True PDF EPUB | 14.4 MB
Democracy's Meanings challenges conventional wisdom regarding how the public thinks about and evaluates democracy. Mining both political theory and more than 75 years of public opinion data, the book argues that Americans think about democracy in ways that go beyond voting or elected representation. Instead, citizens have rich and substantive views about the material conditions that democracy should produce, which draw from their beliefs about equality, fairness, and justice. The authors construct a typology of views about democracy. Procedural views of democracy take a minimalistic quality. While voting and fair treatment are important to this vision of democracy, ideas about equality are mostly limited to civil liberties. In contrast, social views of democracy incorporate both civil and economic equality; according to people with these views, democracy ought to meet the basic social and material needs of citizens. Complementing these two groups are moderate and indifferent views about democracy. While moderate views sit somewhere in between procedural and social perspectives regarding the role of democracy in producing social and economic equality, indifferent views of democracy involve disaffection toward it. For a small group of apathetic citizens, democracy is an ambiguous and ill-defined concept.
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English | 2022 | ISBN: 978-9811957185 | 186 pages | True PDF EPUB | 21.29 MB
This is the first of its kind book that describes key elements of enterprise data and analytics strategy, and prescribes a pragmatic approach to define the strategy for large enterprises. The book is based on successful digital transformation experience of multiple Fortune 500 and other large enterprises. It is estimated that more than 50% of data and analytics initiatives fail globally because of the inherent complexity of such initiatives. Some of the questions that enterprises struggle with are: How to define enterprise data and analytics strategy? What are the key elements that should be considered while doing so? Why one-size-fits-all approach does not work for all enterprises? How to align data and analytics initiative with the business strategy of the CEO? How to establish a futuristic technology and architecture foundation, given the exponential rate of innovation in data and analytics technologies? How to define the right data and analytics organization model? Why data and analytics organization and processes need to be different from other functions? How to manage organizational change to ensure success of data and analytics initiative? How to define a business value measurement framework and calculate ROI from data and analytics initiative? What are the key skills required in a data and analytics leader to wade through political and other challenges of a large enterprise? This book will help executives, chief digital/analytics officers, data and analytics professionals, and consultants, in answering the above questions. It will help them in addressing various dilemmas that they face every day and making their enterprises data-driven.
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English | 2022 | ISBN: 978-1527587281 | 276 pages | True PDF | 12.61 MB
This book contains recent and important results on the deep study of the universe through one of the fields observable that will have a great impact in the next 100 years on space-time research and the creation of future technologies. It will appeal to mathematicians, natural scientists, cosmologists, theoretical physicians, particle physicians, electronics researchers and postgraduate students in mathematical physics dedicated to the study of the universe.
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English | 2022 | ISBN: 1633439844 | 568 pages | True EPUB, MOBI | 137.21 MB
Deep learning from the ground up using R and the powerful Keras library!
In Deep Learning with R, Second Edition you will learn

English | 2022 | ISBN: 1617295442 | 296 pages | True PDF | 9.56 MB
Humans do a great job of reading text, identifying key ideas, summarizing, making connections, and other tasks that require comprehension and context. Recent advances in deep learning make it possible for computer systems to achieve similar results.
Deep Learning for Natural Language Processing teaches you to apply deep learning methods to natural language processing (NLP) to interpret and use text effectively. In this insightful book, NLP expert Stephan Raaijmakers distills his extensive knowledge of the latest state-of-the-art developments in this rapidly emerging field.

English | 2023 | ISBN: 978-8770223898 | 312 pages | True PDF | 30.22 MB
Health care today is known to suffer from siloed and fragmented data, delayed clinical communications, and disparate workflow tools due to the lack of interoperability caused by vendor-locked health care systems, lack of trust among data holders, and security/privacy concerns regarding data sharing. The health information industry is ready for big leaps and bounds in terms of growth and advancement.
This book is an attempt to unveil the hidden potential of the enormous amount of health information and technology. Throughout this book, we attempt to combine numerous compelling views, guidelines, and frameworks to enable personalized health care service options through the successful application of deep learning frameworks. The progress of the health-care sector will be incremental as it learns from associations between data over time through the application of suitable AI, deep net frameworks, and patterns. The major challenge health care is facing is the effective and accurate learning of unstructured clinical data through the application of precise algorithms. Incorrect input data leading to erroneous outputs with false positives is intolerable in healthcare as patients' lives are at stake. This book is written with the intent to uncover the stakes and possibilities involved in realizing personalized health-care services through efficient and effective deep learning algorithms.

English | 2022 | ISBN: 1804615447 | 470 pages | True EPUB | 8.26 MB
Learn concepts, methodologies, and applications of deep learning for building predictive models from complex genomics data sets to overcome challenges in the life sciences and biotechnology industries
Key Features

English | 2022 | ISBN: 1804615447 | 270 pages | True PDF | 15.03 MB
Learn concepts, methodologies, and applications of deep learning for building predictive models from complex genomics data sets to overcome challenges in the life sciences and biotechnology industries
Key Features

English | 2022 | ISBN: 978-0750340229 | 267 pages | True PDF EPUB | 33.76 MB
Artificial intelligence is gaining traction in areas of social responsibility. From climate change to social polarization to epidemics, humankind has been seeking new solutions to these ever-present problems. Deep learning (DL) techniques have increased in power in recent years, with algorithms already exhibiting tremendous possibilities in domains such as scientific research, agriculture, smart cities, finance, healthcare, conservation, the environment, industry and more. Innovative ideas using appropriate DL frameworks are now actively employed for the development of and delivering a positive impact on smart cities and societies. This book highlights the importance of specific frameworks such as IoT-enabled frameworks or serverless cloud frameworks that are applying DL techniques for solving persistent societal problems. It addresses the challenges of DL implementation, computation time, and the complexity of reasoning and modelling different types of data. In particular, the book explores and emphasises techniques involved in DL such as image classification, image enhancement, word analysis, human–machine emotional interfaces and the applications of these techniques for smart cities and societal problems. To extend the theoretical description, the book is enhanced through case studies, including those implemented using tensorflow2 and relevant IoT-specific sensor/actuator frameworks. The broad coverage will be essential reading not just to advanced students and academic researchers but also to practitioners and engineers looking to deliver an improved society and global health. Part of IOP Series in Next Generation Computing.
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