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Coffee Wilt Disease - - Bog - CABI Publishing - Plusbog.dk

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

Sustainable Coffee in Costa Rica - Jeffrey Stratford - Bog - Bloomsbury Publishing PLC - Plusbog.dk

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

Handbook of Coffee Processing By-Products - - Bog - Elsevier Science Publishing Co Inc - Plusbog.dk

Coffee - Growing, Processing, Sustainable Production - - Bog - Wiley-VCH Verlag GmbH - Plusbog.dk

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

Coffee and Coffeehouses - Ralph S. Hattox - Bog - University of Washington Press - Plusbog.dk

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

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

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

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

The Craft and Science of Coffee - - Bog - Elsevier Science Publishing Co Inc - Plusbog.dk

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

Coffee - - Bog - Rowman & Littlefield - Plusbog.dk

Coffee - - Bog - Rowman & Littlefield - Plusbog.dk

Coffee: A Comprehensive Guide to the Bean, the Beverage, and the Industry offers a definitive guide to the many rich dimensions of the bean and the beverage around the world. Leading experts from business and academia consider coffee’s history, global spread, cultivation, preparation, marketing, and the environmental and social issues surrounding it today. They discuss, for example, the impact of globalization; the many definitions of organic, direct trade, and fair trade; the health of female farmers; the relationships among shade, birds, and coffee; roasting as an art and a science; and where profits are made in the commodity chain. Drawing on interviews and the lives of people working in the business—from pickers and roasters to coffee bar owners and consumers—this book brings a compelling human side to the story. The authors avoid romanticizing or demonizing any group in the business. They consider basic but widely misunderstood issues such as who adds value to the bean, the constraints of peasant life, and the impact of climate change. Moving beyond simple answers, they represent various participants in the supply chain and a range of opinions about problems and suggested solutions in the industry. Coffee offers a multidimensional examination of a deceptively everyday but extremely complex commodity that remains at the center of many millions of lives. Tracing coffee’s journey from field to cup, this handbook to one of the world’s favorite beverages is an essential guide for professionals, coffee lovers, and students alike. Contributions by: Sarah Allen, Jonathan D. Baker, Peter S. Baker, Jonathan Wesley Bell, Clare Benfield, H. C. "Skip" Bittenbender, Connie Blumhardt, Willem Boot, Carlos H. J. Brando, August Burns, Luis Alberto Cuéllar, Olga Cuellar, Kenneth Davids, Jim Fadden, Elijah K. Gichuru, Jeremy Haggar, Andrew Hetzel, George Howell, Juliana Jaramillo, Phyllis Johnson, Lawrence W. Jones, Alf Kramer, Ted Lingle, Stuart McCook, Michelle Craig McDonald, Sunalini Menon, Jonathan Morris, Joan Obra, Price Peterson, Rick Peyser, Sergii Reminny, Paul Rice, Robert Rice, Carlos Saenz, Vincenzo Sandalj, Jinap Selamat, Colin Smith, Shawn Steiman, Robert W. Thurston, Steven Topik, Tatsushi Ueshima, Camilla C. Valeur, Geoff Watts, and Britta Zeitemann

DKK 980.00
1

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

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

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