2.300 resultater (0,43990 sekunder)

Vis alle filtre

Mærke

Vis alle

Butik

Pris (EUR)

Nulstil filter

Produkter
Fra
Butikker

Apollo to Apollo - Henrik Bo Andersen - Bog - HBOART ApS - Plusbog.dk

Apollo to Apollo - Henrik Bo Andersen - Bog - HBOART ApS - Plusbog.dk

Inspired by the fresh perspective of a collector and an adventurer, westep into a rare universe of Ancient Miniature Art humbly illuminatingcritical historical principles we have forgotten.A crisp presentation of more than three hundred photographs withdescriptions tiptoes us back to the beginning of Western culture. Wediscover hidden art and artists who were silent visionaries interpretingmessages in astrology, politics, medicine, science, love and emotions.Apollo to Apollo is our ‘wake-up call’ to explore, not just the stars in ourskies, but much closer; the intuitive world of Ancient Miniature Art thatwe, today, can still hold in our hands.

DKK 1119.00
1

Machine Learning for Business Analytics - Galit (university Of Maryland Shmueli - Bog - John Wiley & Sons Inc - Plusbog.dk

Machine Learning for Business Analytics - Galit (university Of Maryland Shmueli - Bog - John Wiley & Sons Inc - Plusbog.dk

MACHINE LEARNING FOR BUSINESS ANALYTICS An up-to-date introduction to a market-leading platform for data analysis and machine learning Machine Learning for Business Analytics: Concepts, Techniques, and Applications with JMP Pro, 2nd ed. offers an accessible and engaging introduction to machine learning. It provides concrete examples and case studies to educate new users and deepen existing users’ understanding of their data and their business. Fully updated to incorporate new topics and instructional material, this remains the only comprehensive introduction to this crucial set of analytical tools specifically tailored to the needs of businesses. Machine Learning for Business Analytics: Concepts, Techniques, and Applications with JMP Pro, 2nd ed. readers will also find: Updated material which improves the book’s usefulness as a reference for professionals beyond the classroomFour new chapters, covering topics including Text Mining and Responsible Data ScienceAn updated companion website with data sets and other instructor resources: www.jmp.com/dataminingbookA guide to JMP Pro's new features and enhanced functionality Machine Learning for Business Analytics: Concepts, Techniques, and Applications with JMP Pro, 2nd ed. is ideal for students and instructors of business analytics and data mining classes, as well as data science practitioners and professionals in data-driven industries.

DKK 979.00
1

Quantum Machine Learning - - Bog - Taylor & Francis Ltd - Plusbog.dk

Quantum Machine Learning - - Bog - Taylor & Francis Ltd - Plusbog.dk

This book presents the research into and application of machine learning in quantum computation, known as quantum machine learning (QML). It presents a comparison of quantum machine learning, classical machine learning, and traditional programming, along with the usage of quantum computing, toward improving traditional machine learning algorithms through case studies. In summary, the book: - - Covers the core and fundamental aspects of statistics, quantum learning, and quantum machines. - - - Discusses the basics of machine learning, regression, supervised and unsupervised machine learning algorithms, and artificial neural networks. - - - Elaborates upon quantum machine learning models, quantum machine learning approaches and quantum classification, and boosting. - - - Introduces quantum evaluation models, deep quantum learning, ensembles, and QBoost. - - - Presents case studies to demonstrate the efficiency of quantum mechanics in industrial aspects. - This reference text is primarily written for scholars and researchers working in the fields of computer science and engineering, information technology, electrical engineering, and electronics and communication engineering.

DKK 901.00
1

Machine Learning for Healthcare - - Bog - Taylor & Francis Ltd - Plusbog.dk

Machine Learning for Healthcare - - Bog - Taylor & Francis Ltd - Plusbog.dk

Machine Learning for Healthcare: Handling and Managing Data provides in-depth information about handling and managing healthcare data through machine learning methods. This book expresses the long-standing challenges in healthcare informatics and provides rational explanations of how to deal with them. Machine Learning for Healthcare: Handling and Managing Data provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of machine learning applications. These are illustrated in a case study which examines how chronic disease is being redefined through patient-led data learning and the Internet of Things. This text offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare. Readers will discover the ethical implications of machine learning in healthcare and the future of machine learning in population and patient health optimization. This book can also help assist in the creation of a machine learning model, performance evaluation, and the operationalization of its outcomes within organizations. It may appeal to computer science/information technology professionals and researchers working in the area of machine learning, and is especially applicable to the healthcare sector. The features of this book include: - - A unique and complete focus on applications of machine learning in the healthcare sector. - - - An examination of how data analysis can be done using healthcare data and bioinformatics. - - - An investigation of how healthcare companies can leverage the tapestry of big data to discover new business values. - - - An exploration of the concepts of machine learning, along with recent research developments in healthcare sectors. -

DKK 993.00
1

Cyber Security Meets Machine Learning - - Bog - Springer Verlag, Singapore - Plusbog.dk

Cyber Security Meets Machine Learning - - Bog - Springer Verlag, Singapore - Plusbog.dk

Machine learning boosts the capabilities of security solutions in the modern cyber environment. However, there are also security concerns associated with machine learning models and approaches: the vulnerability of machine learning models to adversarial attacks is a fatal flaw in the artificial intelligence technologies, and the privacy of the data used in the training and testing periods is also causing increasing concern among users. This book reviews the latest research in the area, including effective applications of machine learning methods in cybersecurity solutions and the urgent security risks related to the machine learning models. The book is divided into three parts: Cyber Security Based on Machine Learning; Security in Machine Learning Methods and Systems; and Security and Privacy in Outsourced Machine Learning. Addressing hot topics in cybersecurity and written by leading researchers in the field, the book features self-contained chapters to allow readers to select topics that are relevant to their needs. It is a valuable resource for all those interested in cybersecurity and robust machine learning, including graduate students and academic and industrial researchers, wanting to gain insights into cutting-edge research topics, as well as related tools and inspiring innovations.

DKK 816.00
1

Machine Learning in Clinical Neuroscience - - Bog - Springer Nature Switzerland AG - Plusbog.dk

Machine Learning in Clinical Neuroscience - - Bog - Springer Nature Switzerland AG - Plusbog.dk

This book bridges the gap between data scientists and clinicians by introducing all relevant aspects of machine learning in an accessible way, and will certainly foster new and serendipitous applications of machine learning in the clinical neurosciences. Building from the ground up by communicating the foundational knowledge and intuitions first before progressing to more advanced and specific topics, the book is well-suited even for clinicians without prior machine learning experience. Authored by a wide array of experienced global machine learning groups, the book is aimed at clinicians who are interested in mastering the basics of machine learning and who wish to get started with their own machine learning research. The volume is structured in two major parts: The first uniquely introduces all major concepts in clinical machine learning from the ground up, and includes step-by-step instructions on how to correctly develop and validate clinical prediction models. It also includes methodological and conceptual foundations of other applications of machine learning in clinical neuroscience, such as applications of machine learning to neuroimaging, natural language processing, and time series analysis. The second part provides an overview of some state-of-the-art applications of these methodologies. The Machine Intelligence in Clinical Neuroscience (MICN) Laboratory at the Department of Neurosurgery of the University Hospital Zurich studies clinical applications of machine intelligence to improve patient care in clinical neuroscience. The group focuses on diagnostic, prognostic and predictive analytics that aid in decision-making by increasing objectivity and transparency to patients. Other major interests of our group members are in medical imaging, and intraoperative applications of machine vision.

DKK 986.00
1

Machine Guarding Handbook - Frank R. Spellman - Bog - Government Institutes - Plusbog.dk

Machine Guarding Handbook - Frank R. Spellman - Bog - Government Institutes - Plusbog.dk

Machine Guarding Handbook is a must-have reading for safety engineers and managers in manufacturing and other industrial settings who need to incorporate an effective machine guarding safety program, meet OSHA requirements, and protect workers. It provides a basic overview of OSHA''s requirements, making compliance easier to achieve, thus preventing the risk of worker injury or mutilation and reducing the occurrence of costly penalties and OSHA audits. This 106-page book explores and discusses the hazards of unguarded machines, common safeguarding methods, the safeguarding of machines and robots, the importance of guarding, the varying methods of machine guarding, training, inspection and maintenance, and safeguarding techniques. In addition, it provides both regulatory information and the material required to implement a viable machine guarding program. Special features include a sample lockout/tagout program, checklists, a machine-guarding case study, chapter summaries, and the complete OSHA Machine Guarding and Lockout/Tagout Standards.

DKK 936.00
1

Machine Learning and Wireless Communications - - Bog - Cambridge University Press - Plusbog.dk

Machine Learning and Wireless Communications - - Bog - Cambridge University Press - Plusbog.dk

How can machine learning help the design of future communication networks – and how can future networks meet the demands of emerging machine learning applications? Discover the interactions between two of the most transformative and impactful technologies of our age in this comprehensive book. First, learn how modern machine learning techniques, such as deep neural networks, can transform how we design and optimize future communication networks. Accessible introductions to concepts and tools are accompanied by numerous real-world examples, showing you how these techniques can be used to tackle longstanding problems. Next, explore the design of wireless networks as platforms for machine learning applications – an overview of modern machine learning techniques and communication protocols will help you to understand the challenges, while new methods and design approaches will be presented to handle wireless channel impairments such as noise and interference, to meet the demands of emerging machine learning applications at the wireless edge.

DKK 819.00
1

Machine Learning for Neuroscience - Chuck Easttom - Bog - Taylor & Francis Ltd - Plusbog.dk

Machine Learning for Neuroscience - Chuck Easttom - Bog - Taylor & Francis Ltd - Plusbog.dk

This book addresses the growing need for machine learning and data mining in neuroscience. The book offers a basic overview of the neuroscience, machine learning and the required math and programming necessary to develop reliable working models. The material is presented in a easy to follow user-friendly manner and is replete with fully working machine learning code. Machine Learning for Neuroscience: A Systematic Approach, tackles the needs of neuroscience researchers and practitioners that have very little training relevant to machine learning. The first section of the book provides an overview of necessary topics in order to delve into machine learning, including basic linear algebra and Python programming. The second section provides an overview of neuroscience and is directed to the computer science oriented readers. The section covers neuroanatomy and physiology, cellular neuroscience, neurological disorders and computational neuroscience. The third section of the book then delves into how to apply machine learning and data mining to neuroscience and provides coverage of artificial neural networks (ANN), clustering, and anomaly detection. The book contains fully working code examples with downloadable working code. It also contains lab assignments and quizzes, making it appropriate for use as a textbook. The primary audience is neuroscience researchers who need to delve into machine learning, programmers assigned neuroscience related machine learning projects and students studying methods in computational neuroscience.

DKK 929.00
1

Human and Machine Learning - - Bog - Springer International Publishing AG - Plusbog.dk

Human and Machine Learning - - Bog - Springer International Publishing AG - Plusbog.dk

With an evolutionary advancement of Machine Learning (ML) algorithms, a rapid increase of data volumes and a significant improvement of computation powers, machine learning becomes hot in different applications. However, because of the nature of "black-box" in ML methods, ML still needs to be interpreted to link human and machine learning for transparency and user acceptance of delivered solutions. This edited book addresses such links from the perspectives of visualisation, explanation, trustworthiness and transparency. The book establishes the link between human and machine learning by exploring transparency in machine learning, visual explanation of ML processes, algorithmic explanation of ML models, human cognitive responses in ML-based decision making, human evaluation of machine learning and domain knowledge in transparent ML applications. This is the first book of its kind to systematically understand the current active research activities and outcomes related to human and machine learning. The book will not only inspire researchers to passionately develop new algorithms incorporating human for human-centred ML algorithms, resulting in the overall advancement of ML, but also help ML practitioners proactively use ML outputs for informative and trustworthy decision making. This book is intended for researchers and practitioners involved with machine learning and its applications. The book will especially benefit researchers in areas like artificial intelligence, decision support systems and human-computer interaction.

DKK 988.00
1

Machine Learning Applications - - Bog - John Wiley & Sons Inc - Plusbog.dk

Machine Learning Applications - - Bog - John Wiley & Sons Inc - Plusbog.dk

Machine Learning Applications Practical resource on the importance of Machine Learning and Deep Learning applications in various technologies and real-world situations Machine Learning Applications discusses methodological advancements of machine learning and deep learning, presents applications in image processing, including face and vehicle detection, image classification, object detection, image segmentation, and delivers real-world applications in healthcare to identify diseases and diagnosis, such as creating smart health records and medical imaging diagnosis, and provides real-world examples, case studies, use cases, and techniques to enable the reader’s active learning. Composed of 13 chapters, this book also introduces real-world applications of machine and deep learning in blockchain technology, cyber security, and climate change. An explanation of AI and robotic applications in mechanical design is also discussed, including robot-assisted surgeries, security, and space exploration. The book describes the importance of each subject area and detail why they are so important to us from a societal and human perspective. Edited by two highly qualified academics and contributed to by established thought leaders in their respective fields, Machine Learning Applications includes information on: Content based medical image retrieval (CBMIR), covering face and vehicle detection, multi-resolution and multisource analysis, manifold and image processing, and morphological processing Smart medicine, including machine learning and artificial intelligence in medicine, risk identification, tailored interventions, and association rules AI and robotics application for transportation and infrastructure (e.g., autonomous cars and smart cities), along with global warming and climate change Identifying diseases and diagnosis, drug discovery and manufacturing, medical imaging diagnosis, personalized medicine, and smart health records With its practical approach to the subject, Machine Learning Applications is an ideal resource for professionals working with smart technologies such as machine and deep learning, AI, IoT, and other wireless communications; it is also highly suitable for professionals working in robotics, computer vision, cyber security and more.

DKK 923.00
1

An Introduction to Machine Learning - Sanjay Churiwala - Bog - Springer Nature Switzerland AG - Plusbog.dk

An Introduction to Machine Learning - Sanjay Churiwala - Bog - Springer Nature Switzerland AG - Plusbog.dk

Just like electricity, Machine Learning will revolutionize our life in many ways - some of which are not even conceivable today. This book provides a thorough conceptual understanding of Machine Learning techniques and algorithms. Many of the mathematical concepts are explained in an intuitive manner. The book starts with an overview of machine learning and the underlying Mathematical and Statistical concepts before moving onto machine learning topics. It gradually builds up the depth, covering many of the present day machine learning algorithms, ending in Deep Learning and Reinforcement Learning algorithms. The book also covers some of the popular Machine Learning applications. The material in this book is agnostic to any specific programming language or hardware so that readers can try these concepts on whichever platforms they are already familiar with. - Offers a comprehensive introduction to Machine Learning, while not assuming any prior knowledge of the topic; - Provides a complete overview of available techniques and algorithms in conceptual terms, covering various application domains of machine learning; - Not tied to any specific software language or hardware implementation.

DKK 986.00
1

Italian Futurism and the Machine - Katia Pizzi - Bog - Manchester University Press - Plusbog.dk

Italian Futurism and the Machine - Katia Pizzi - Bog - Manchester University Press - Plusbog.dk

This is the first interdisciplinary exploration of machine culture in Italian futurism after the First World War. The machine was a primary concern for the futuristi. As well as being a material tool in the factory it was a social and political agent, an aesthetic emblem, a metonymy of modernity and international circulation and a living symbol of past crafts and technologies. Exploring literature, the visual and performing arts, photography, music and film, the book uses the lens of European machine culture to elucidate the work of a broad set of artists and practitioners, including Censi, Depero, Marinetti, Munari and Prampolini. The machine emerges here as an archaeology of technology in modernity: the time machine of futurism.

DKK 788.00
1

Machine Learning and the City - S Carta - Bog - John Wiley and Sons Ltd - Plusbog.dk

Machine Learning and the City - S Carta - Bog - John Wiley and Sons Ltd - Plusbog.dk

Machine Learning and the City Explore the applications of machine learning and artificial intelligence to the built environment Machine Learning and the City: Applications in Architecture and Urban Design delivers a robust exploration of machine learning (ML) and artificial intelligence (AI) in the context of the built environment. Relevant contributions from leading scholars in their respective fields describe the ideas and techniques that underpin ML and AI, how to begin using ML and AI in urban design, and the likely impact of ML and AI on the future of city design and planning. Each section couples theoretical and technical chapters, authoritative references, and concrete examples and projects that illustrate the efficacy and power of machine learning in urban design. The book also includes: An introduction to the probabilistic logic that underpins machine learningComprehensive explorations of the applications of machine learning and artificial intelligence to urban environmentsPractical discussions of the consequences of applied machine learning and the future of urban design Perfect for designers approaching machine learning and AI for the first time, Machine Learning and the City: Applications in Architecture and Urban Design will also earn a place in the libraries of urban planners and engineers involved in urban design.

DKK 804.00
1

Cost-Sensitive Machine Learning - - Bog - Taylor & Francis Inc - Plusbog.dk

Cost-Sensitive Machine Learning - - Bog - Taylor & Francis Inc - Plusbog.dk

In machine learning applications, practitioners must take into account the cost associated with the algorithm. These costs include: - Cost of acquiring training data Cost of data annotation/labeling and cleaning Computational cost for model fitting, validation, and testing Cost of collecting features/attributes for test data Cost of user feedback collection Cost of incorrect prediction/classification Cost-Sensitive Machine Learning is one of the first books to provide an overview of the current research efforts and problems in this area. It discusses real-world applications that incorporate the cost of learning into the modeling process. The first part of the book presents the theoretical underpinnings of cost-sensitive machine learning. It describes well-established machine learning approaches for reducing data acquisition costs during training as well as approaches for reducing costs when systems must make predictions for new samples. The second part covers real-world applications that effectively trade off different types of costs. These applications not only use traditional machine learning approaches, but they also incorporate cutting-edge research that advances beyond the constraining assumptions by analyzing the application needs from first principles. Spurring further research on several open problems, this volume highlights the often implicit assumptions in machine learning techniques that were not fully understood in the past. The book also illustrates the commercial importance of cost-sensitive machine learning through its coverage of the rapid application developments made by leading companies and academic research labs.

DKK 958.00
1

Statistical Machine Learning - Richard Golden - Bog - Taylor & Francis Ltd - Plusbog.dk

Statistical Machine Learning - Richard Golden - Bog - Taylor & Francis Ltd - Plusbog.dk

The recent rapid growth in the variety and complexity of new machine learning architectures requires the development of improved methods for designing, analyzing, evaluating, and communicating machine learning technologies. Statistical Machine Learning: A Unified Framework provides students, engineers, and scientists with tools from mathematical statistics and nonlinear optimization theory to become experts in the field of machine learning. In particular, the material in this text directly supports the mathematical analysis and design of old, new, and not-yet-invented nonlinear high-dimensional machine learning algorithms. Features: - - - Unified empirical risk minimization framework supports rigorous mathematical analyses of widely used supervised, unsupervised, and reinforcement machine learning algorithms - - - Matrix calculus methods for supporting machine learning analysis and design applications - - - Explicit conditions for ensuring convergence of adaptive, batch, minibatch, MCEM, and MCMC learning algorithms that minimize both unimodal and multimodal objective functions - - - Explicit conditions for characterizing asymptotic properties of M-estimators and model selection criteria such as AIC and BIC in the presence of possible model misspecification - This advanced text is suitable for graduate students or highly motivated undergraduate students in statistics, computer science, electrical engineering, and applied mathematics. The text is self-contained and only assumes knowledge of lower-division linear algebra and upper-division probability theory. Students, professional engineers, and multidisciplinary scientists possessing these minimal prerequisites will find this text challenging yet accessible. About the Author: Richard M. Golden (Ph.D., M.S.E.E., B.S.E.E.) is Professor of Cognitive Science and Participating Faculty Member in Electrical Engineering at the University of Texas at Dallas. Dr. Golden has published articles and given talks at scientific conferences on a wide range of topics in the fields of both statistics and machine learning over the past three decades. His long-term research interests include identifying conditions for the convergence of deterministic and stochastic machine learning algorithms and investigating estimation and inference in the presence of possibly misspecified probability models.

DKK 993.00
1

Machine Learning for Cyber Security - - Bog - Springer Nature Switzerland AG - Plusbog.dk

Machine Learning for Cyber Security - - Bog - Springer Nature Switzerland AG - Plusbog.dk

This three volume book set constitutes the proceedings of the Third International Conference on Machine Learning for Cyber Security, ML4CS 2020, held in Xi''an, China in October 2020. The 118 full papers and 40 short papers presented were carefully reviewed and selected from 360 submissions. The papers offer a wide range of the following subjects: Machine learning, security, privacy-preserving, cyber security, Adversarial machine Learning, Malware detection and analysis, Data mining, and Artificial Intelligence.

DKK 800.00
1

Machine Learning for Cyber Security - - Bog - Springer Nature Switzerland AG - Plusbog.dk

Machine Learning for Cyber Security - - Bog - Springer Nature Switzerland AG - Plusbog.dk

This three volume book set constitutes the proceedings of the Third International Conference on Machine Learning for Cyber Security, ML4CS 2020, held in Xi''an, China in October 2020. The 118 full papers and 40 short papers presented were carefully reviewed and selected from 360 submissions. The papers offer a wide range of the following subjects: Machine learning, security, privacy-preserving, cyber security, Adversarial machine Learning, Malware detection and analysis, Data mining, and Artificial Intelligence.

DKK 967.00
1