Innovations and Applications of AI, IoT, and Cognitive Technologies

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Publisher :
ISBN 13 : 9781799868712
Total Pages : pages
Book Rating : 4.8/5 (687 download)

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Book Synopsis Innovations and Applications of AI, IoT, and Cognitive Technologies by : Jingyuan Zhao

Download or read book Innovations and Applications of AI, IoT, and Cognitive Technologies written by Jingyuan Zhao and published by . This book was released on 2021-02 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Computer Vision and Recognition Systems

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Publisher : CRC Press
ISBN 13 : 1000400778
Total Pages : 272 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Computer Vision and Recognition Systems by : Chiranji Lal Chowdhary

Download or read book Computer Vision and Recognition Systems written by Chiranji Lal Chowdhary and published by CRC Press. This book was released on 2022-03-10 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This cutting-edge volume focuses on how artificial intelligence can be used to give computers the ability to imitate human sight. With contributions from researchers in diverse countries, including Thailand, Spain, Japan, Turkey, Australia, and India, the book explains the essential modules that are necessary for comprehending artificial intelligence experiences to provide machines with the power of vision. The volume also presents innovative research developments, applications, and current trends in the field. The chapters cover such topics as visual quality improvement, Parkinson’s disease diagnosis, hypertensive retinopathy detection through retinal fundus, big image data processing, N-grams for image classification, medical brain images, chatbot applications, credit score improvisation, vision-based vehicle lane detection, damaged vehicle parts recognition, partial image encryption of medical images, and image synthesis. The chapter authors show different approaches to computer vision, image processing, and frameworks for machine learning to build automated and stable applications. Deep learning is included for making immersive application-based systems, pattern recognition, and biometric systems. The book also considers efficiency and comparison at various levels of using algorithms for real-time applications, processes, and analysis.

Cyber Security and Digital Forensics

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Publisher : John Wiley & Sons
ISBN 13 : 1119795648
Total Pages : 300 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Cyber Security and Digital Forensics by : Sabyasachi Pramanik

Download or read book Cyber Security and Digital Forensics written by Sabyasachi Pramanik and published by John Wiley & Sons. This book was released on 2022-01-12 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: CYBER SECURITY AND DIGITAL FORENSICS Cyber security is an incredibly important issue that is constantly changing, with new methods, processes, and technologies coming online all the time. Books like this are invaluable to professionals working in this area, to stay abreast of all of these changes. Current cyber threats are getting more complicated and advanced with the rapid evolution of adversarial techniques. Networked computing and portable electronic devices have broadened the role of digital forensics beyond traditional investigations into computer crime. The overall increase in the use of computers as a way of storing and retrieving high-security information requires appropriate security measures to protect the entire computing and communication scenario worldwide. Further, with the introduction of the internet and its underlying technology, facets of information security are becoming a primary concern to protect networks and cyber infrastructures from various threats. This groundbreaking new volume, written and edited by a wide range of professionals in this area, covers broad technical and socio-economic perspectives for the utilization of information and communication technologies and the development of practical solutions in cyber security and digital forensics. Not just for the professional working in the field, but also for the student or academic on the university level, this is a must-have for any library. Audience: Practitioners, consultants, engineers, academics, and other professionals working in the areas of cyber analysis, cyber security, homeland security, national defense, the protection of national critical infrastructures, cyber-crime, cyber vulnerabilities, cyber-attacks related to network systems, cyber threat reduction planning, and those who provide leadership in cyber security management both in public and private sectors

Deep Learning Applications, Volume 2

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Publisher : Springer
ISBN 13 : 9789811567582
Total Pages : 300 pages
Book Rating : 4.5/5 (675 download)

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Book Synopsis Deep Learning Applications, Volume 2 by : M. Arif Wani

Download or read book Deep Learning Applications, Volume 2 written by M. Arif Wani and published by Springer. This book was released on 2020-12-14 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents selected papers from the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019). It focuses on deep learning networks and their application in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments, and highlights novel ways of using deep neural networks to solve real-world problems. Also offering insights into deep learning architectures and algorithms, it is an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers.

The Economics of Artificial Intelligence

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Publisher : University of Chicago Press
ISBN 13 : 0226833127
Total Pages : 172 pages
Book Rating : 4.2/5 (268 download)

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Book Synopsis The Economics of Artificial Intelligence by : Ajay Agrawal

Download or read book The Economics of Artificial Intelligence written by Ajay Agrawal and published by University of Chicago Press. This book was released on 2024-03-05 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.

Innovations in Machine and Deep Learning

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Publisher : Springer Nature
ISBN 13 : 3031406885
Total Pages : 506 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis Innovations in Machine and Deep Learning by : Gilberto Rivera

Download or read book Innovations in Machine and Deep Learning written by Gilberto Rivera and published by Springer Nature. This book was released on 2023-11-04 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, significant progress has been made in achieving artificial intelligence (AI) with an impact on students, managers, scientists, health personnel, technical roles, investors, teachers, and leaders. This book presents numerous successful applications of AI in various contexts. The innovative implications covered fall under the general field of machine learning (ML), including deep learning, decision-making, forecasting, pattern recognition, information retrieval, and interpretable AI. Decision-makers and entrepreneurs will find numerous successful applications in health care, sustainability, risk management, human activity recognition, logistics, and Industry 4.0. This book is an essential resource for anyone interested in challenges, opportunities, and the latest developments and real-world applications of ML. Whether you are a student, researcher, practitioner, or simply curious about AI, this book provides valuable insights and inspiration for your work and learning.

Deploying Machine Learning

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Publisher : Addison-Wesley Professional
ISBN 13 : 9780135226209
Total Pages : 99998 pages
Book Rating : 4.2/5 (262 download)

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Book Synopsis Deploying Machine Learning by : Robbie Allen

Download or read book Deploying Machine Learning written by Robbie Allen and published by Addison-Wesley Professional. This book was released on 2019-05 with total page 99998 pages. Available in PDF, EPUB and Kindle. Book excerpt: Increasingly, business leaders and managers recognize that machine learning offers their companies immense opportunities for competitive advantage. But most discussions of machine learning are intensely technical or academic, and don't offer practical information leaders can use to identify, evaluate, plan, or manage projects. Deploying Machine Learning fills that gap, helping them clarify exactly how machine learning can help them, and collaborate with technologists to actually apply it successfully. You'll learn: What machine learning is, how it compares to "big data" and "artificial intelligence," and why it's suddenly so important What machine learning can do for you: solutions for computer vision, natural language processing, prediction, and more How to use machine learning to solve real business problems -- from reducing costs through improving decision-making and introducing new products Separating hype from reality: identifying pitfalls, limitations, and misconceptions upfront Knowing enough about the technology to work effectively with your technical team Getting the data right: sourcing, collection, governance, security, and culture Solving harder problems: exploring deep learning and other advanced techniques Understanding today's machine learning software and hardware ecosystem Evaluating potential projects, and addressing workforce concerns Staffing your project, acquiring the right tools, and building a workable project plan Interpreting results -- and building an organization that can increasingly learn from data Using machine learning responsibly and ethically Preparing for tomorrow's advances The authors conclude with five chapter-length case studies: image, text, and video analysis, chatbots, and prediction applications. For each, they don't just present results: they also illuminate the process the company undertook, and the pitfalls it overcame along the way.

Artificial Intelligence in Healthcare

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Publisher : Academic Press
ISBN 13 : 0128184396
Total Pages : 385 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Artificial Intelligence in Healthcare by : Adam Bohr

Download or read book Artificial Intelligence in Healthcare written by Adam Bohr and published by Academic Press. This book was released on 2020-06-21 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data

Data Science and Innovations for Intelligent Systems

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Publisher : CRC Press
ISBN 13 : 1000456153
Total Pages : 385 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Data Science and Innovations for Intelligent Systems by : Kavita Taneja

Download or read book Data Science and Innovations for Intelligent Systems written by Kavita Taneja and published by CRC Press. This book was released on 2021-09-30 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data science is an emerging field and innovations in it need to be explored for the success of society 5.0. This book not only focuses on the practical applications of data science to achieve computational excellence, but also digs deep into the issues and implications of intelligent systems. This book highlights innovations in data science to achieve computational excellence that can optimize performance of smart applications. The book focuses on methodologies, framework, design issues, tools, architectures, and technologies necessary to develop and understand data science and its emerging applications in the present era. Data Science and Innovations for Intelligent Systems: Computational Excellence and Society 5.0 is useful for the research community, start-up entrepreneurs, academicians, data-centered industries, and professeurs who are interested in exploring innovations in varied applications and the areas of data science.

Advances in Intelligent Systems Research and Innovation

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Publisher : Springer Nature
ISBN 13 : 3030781240
Total Pages : 489 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Advances in Intelligent Systems Research and Innovation by : Vassil Sgurev

Download or read book Advances in Intelligent Systems Research and Innovation written by Vassil Sgurev and published by Springer Nature. This book was released on 2021-11-03 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book represents the experience of successful researchers from four continents on a broad range of intelligent systems, and it hints how to avoid anticipated conflicts and problems during multidisciplinary innovative research from Industry 4.0 and/or Internet of Things through modern machine learning, and software agent applications to open data science big data/advance analytics/visual analytics/text mining/web mining/knowledge discovery/deep data mining issues. The considered intelligent part is essential in most smart/control systems, cyber security, bioinformatics, virtual reality, robotics, mathematical modelling projects, and its significance rapidly increases in other technologies. Theoretical foundations of fuzzy sets, mathematical and non-classical logic also are rapidly developing.

Deep Learning for Vision Systems

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Publisher : Manning Publications
ISBN 13 : 1617296198
Total Pages : 478 pages
Book Rating : 4.6/5 (172 download)

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Book Synopsis Deep Learning for Vision Systems by : Mohamed Elgendy

Download or read book Deep Learning for Vision Systems written by Mohamed Elgendy and published by Manning Publications. This book was released on 2020-11-10 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: How does the computer learn to understand what it sees? Deep Learning for Vision Systems answers that by applying deep learning to computer vision. Using only high school algebra, this book illuminates the concepts behind visual intuition. You'll understand how to use deep learning architectures to build vision system applications for image generation and facial recognition. Summary Computer vision is central to many leading-edge innovations, including self-driving cars, drones, augmented reality, facial recognition, and much, much more. Amazing new computer vision applications are developed every day, thanks to rapid advances in AI and deep learning (DL). Deep Learning for Vision Systems teaches you the concepts and tools for building intelligent, scalable computer vision systems that can identify and react to objects in images, videos, and real life. With author Mohamed Elgendy's expert instruction and illustration of real-world projects, you’ll finally grok state-of-the-art deep learning techniques, so you can build, contribute to, and lead in the exciting realm of computer vision! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology How much has computer vision advanced? One ride in a Tesla is the only answer you’ll need. Deep learning techniques have led to exciting breakthroughs in facial recognition, interactive simulations, and medical imaging, but nothing beats seeing a car respond to real-world stimuli while speeding down the highway. About the book How does the computer learn to understand what it sees? Deep Learning for Vision Systems answers that by applying deep learning to computer vision. Using only high school algebra, this book illuminates the concepts behind visual intuition. You'll understand how to use deep learning architectures to build vision system applications for image generation and facial recognition. What's inside Image classification and object detection Advanced deep learning architectures Transfer learning and generative adversarial networks DeepDream and neural style transfer Visual embeddings and image search About the reader For intermediate Python programmers. About the author Mohamed Elgendy is the VP of Engineering at Rakuten. A seasoned AI expert, he has previously built and managed AI products at Amazon and Twilio. Table of Contents PART 1 - DEEP LEARNING FOUNDATION 1 Welcome to computer vision 2 Deep learning and neural networks 3 Convolutional neural networks 4 Structuring DL projects and hyperparameter tuning PART 2 - IMAGE CLASSIFICATION AND DETECTION 5 Advanced CNN architectures 6 Transfer learning 7 Object detection with R-CNN, SSD, and YOLO PART 3 - GENERATIVE MODELS AND VISUAL EMBEDDINGS 8 Generative adversarial networks (GANs) 9 DeepDream and neural style transfer 10 Visual embeddings

Deep Learning

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Publisher : MIT Press
ISBN 13 : 0262337371
Total Pages : 801 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Deep Learning by : Ian Goodfellow

Download or read book Deep Learning written by Ian Goodfellow and published by MIT Press. This book was released on 2016-11-10 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

Information Technology Innovation

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Publisher : National Academies Press
ISBN 13 : 0309684234
Total Pages : 148 pages
Book Rating : 4.3/5 (96 download)

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Book Synopsis Information Technology Innovation by : National Academies of Sciences, Engineering, and Medicine

Download or read book Information Technology Innovation written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2020-11-30 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information technology (IT) is widely understood to be the enabling technology of the 21st century. IT has transformed, and continues to transform, all aspects of our lives: commerce and finance, education, energy, health care, manufacturing, government, national security, transportation, communications, entertainment, science, and engineering. IT and its impact on the U.S. economyâ€"both directly (the IT sector itself) and indirectly (other sectors that are powered by advances in IT)â€"continue to grow in size and importance. IT’s impacts on the U.S. economyâ€"both directly (the IT sector itself) and indirectly (other sectors that are powered by advances in IT)â€"continue to grow. IT enabled innovation and advances in IT products and services draw on a deep tradition of research and rely on sustained investment and a uniquely strong partnership in the United States among government, industry, and universities. Past returns on federal investments in IT research have been extraordinary for both U.S. society and the U.S. economy. This IT innovation ecosystem fuels a virtuous cycle of innovation with growing economic impact. Building on previous National Academies work, this report describes key features of the IT research ecosystem that fuel IT innovation and foster widespread and longstanding impact across the U.S. economy. In addition to presenting established computing research areas and industry sectors, it also considers emerging candidates in both categories.

Artificial Intelligence

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Publisher : HBR Insights
ISBN 13 : 9781633697898
Total Pages : 160 pages
Book Rating : 4.6/5 (978 download)

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Book Synopsis Artificial Intelligence by : Harvard Business Review

Download or read book Artificial Intelligence written by Harvard Business Review and published by HBR Insights. This book was released on 2019 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: Companies that don't use AI to their advantage will soon be left behind. Artificial intelligence and machine learning will drive a massive reshaping of the economy and society. What should you and your company be doing right now to ensure that your business is poised for success? These articles by AI experts and consultants will help you understand today's essential thinking on what AI is capable of now, how to adopt it in your organization, and how the technology is likely to evolve in the near future. Artificial Intelligence: The Insights You Need from Harvard Business Review will help you spearhead important conversations, get going on the right AI initiatives for your company, and capitalize on the opportunity of the machine intelligence revolution. Catch up on current topics and deepen your understanding of them with the Insights You Need series from Harvard Business Review. Featuring some of HBR's best and most recent thinking, Insights You Need titles are both a primer on today's most pressing issues and an extension of the conversation, with interesting research, interviews, case studies, and practical ideas to help you explore how a particular issue will impact your company and what it will mean for you and your business.

Artificial Intelligence Applications and Innovations

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Publisher :
ISBN 13 : 9783030791513
Total Pages : 0 pages
Book Rating : 4.7/5 (915 download)

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Book Synopsis Artificial Intelligence Applications and Innovations by : Ilias Maglogiannis

Download or read book Artificial Intelligence Applications and Innovations written by Ilias Maglogiannis and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 17th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2021, held virtually and in Hersonissos, Crete, Greece, in June 2021. The 50 full papers and 11 short papers presented were carefully reviewed and selected from 113 submissions. They cover a broad range of topics related to technical, legal, and ethical aspects of artificial intelligence systems and their applications and are organized in the following sections: adaptive modeling/ neuroscience; AI in biomedical applications; AI impacts/ big data; automated machine learning; autonomous agents; clustering; convolutional NN; data mining/ word counts; deep learning; fuzzy modeling; hyperdimensional computing; Internet of Things/ Internet of energy; machine learning; multi-agent systems; natural language; recommendation systems; sentiment analysis; and smart blockchain applications/ cybersecurity. Chapter "Improving the Flexibility of Production Scheduling in Flat Steel Production Through Standard and AI-based Approaches: Challenges and Perspective" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

The SAGE Handbook of Social Media

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Publisher : SAGE
ISBN 13 : 1473995795
Total Pages : 945 pages
Book Rating : 4.4/5 (739 download)

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Book Synopsis The SAGE Handbook of Social Media by : Jean Burgess

Download or read book The SAGE Handbook of Social Media written by Jean Burgess and published by SAGE. This book was released on 2017-11-20 with total page 945 pages. Available in PDF, EPUB and Kindle. Book excerpt: The world is in the midst of a social media paradigm. Once viewed as trivial and peripheral, social media platforms like Twitter, Facebook and WeChat have become an important part of the information and communication infrastructure of society. They are bound up with business and politics as well as everyday life, work, and personal relationships. This international Handbook addresses the most significant research themes, methodological approaches and debates in the study of social media. It contains substantial chapters written especially for this book by leading scholars from a range of disciplinary perspectives, covering everything from computational social science to sexual self-expression. Part 1: Histories And Pre-Histories Part 2: Approaches And Methods Part 3: Platforms, Technologies And Business Models Part 4: Cultures And Practices Part 5: Social And Economic Domains

Deep Learning for the Life Sciences

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Publisher : O'Reilly Media
ISBN 13 : 1492039802
Total Pages : 236 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Deep Learning for the Life Sciences by : Bharath Ramsundar

Download or read book Deep Learning for the Life Sciences written by Bharath Ramsundar and published by O'Reilly Media. This book was released on 2019-04-10 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning has already achieved remarkable results in many fields. Now it’s making waves throughout the sciences broadly and the life sciences in particular. This practical book teaches developers and scientists how to use deep learning for genomics, chemistry, biophysics, microscopy, medical analysis, and other fields. Ideal for practicing developers and scientists ready to apply their skills to scientific applications such as biology, genetics, and drug discovery, this book introduces several deep network primitives. You’ll follow a case study on the problem of designing new therapeutics that ties together physics, chemistry, biology, and medicine—an example that represents one of science’s greatest challenges. Learn the basics of performing machine learning on molecular data Understand why deep learning is a powerful tool for genetics and genomics Apply deep learning to understand biophysical systems Get a brief introduction to machine learning with DeepChem Use deep learning to analyze microscopic images Analyze medical scans using deep learning techniques Learn about variational autoencoders and generative adversarial networks Interpret what your model is doing and how it’s working